diff --git a/.github/workflows/python-lint.yml b/.github/workflows/python-lint.yml
index f4ae654959be36..5be17f1576ebbc 100644
--- a/.github/workflows/python-lint.yml
+++ b/.github/workflows/python-lint.yml
@@ -21,4 +21,4 @@ jobs:
         uses: py-actions/flake8@v2
         with:
             ignore: "E203,E211,E221,E225,E231,E241,E251,E261,E266,E501,E701,E704,W503"
-            exclude: "examples/*,examples/*/**,*/**/__init__.py"
+            exclude: "examples/*,examples/*/**,*/**/__init__.py,convert-hf-to-gguf-update.py"
diff --git a/.gitignore b/.gitignore
index 5c149008444351..60f9d1f8d04b92 100644
--- a/.gitignore
+++ b/.gitignore
@@ -108,3 +108,18 @@ examples/server/*.mjs.hpp
 poetry.lock
 poetry.toml
 nppBackup
+
+# Test binaries
+/tests/test-grammar-parser
+/tests/test-llama-grammar
+/tests/test-double-float
+/tests/test-grad0
+/tests/test-opt
+/tests/test-quantize-fns
+/tests/test-quantize-perf
+/tests/test-sampling
+/tests/test-tokenizer-0
+/tests/test-tokenizer-1-spm
+/tests/test-tokenizer-1-bpe
+/tests/test-rope
+/tests/test-backend-ops
diff --git a/Makefile b/Makefile
index e169cae88895a9..0a73f2a582a204 100644
--- a/Makefile
+++ b/Makefile
@@ -6,11 +6,23 @@ BUILD_TARGETS = \
 
 # Binaries only useful for tests
 TEST_TARGETS = \
-	tests/test-llama-grammar tests/test-grammar-parser tests/test-double-float tests/test-grad0 tests/test-opt \
-	tests/test-quantize-fns tests/test-quantize-perf tests/test-sampling tests/test-tokenizer-0-llama          \
-	tests/test-tokenizer-0-falcon tests/test-tokenizer-1-llama tests/test-tokenizer-1-bpe tests/test-rope      \
-	tests/test-backend-ops tests/test-model-load-cancel tests/test-autorelease                                 \
-	tests/test-json-schema-to-grammar tests/test-grammar-integration
+	tests/test-autorelease \
+	tests/test-backend-ops \
+	tests/test-double-float \
+	tests/test-grad0 \
+	tests/test-grammar-integration \
+	tests/test-grammar-parser \
+	tests/test-json-schema-to-grammar \
+	tests/test-llama-grammar \
+	tests/test-model-load-cancel \
+	tests/test-opt \
+	tests/test-quantize-fns \
+	tests/test-quantize-perf \
+	tests/test-rope \
+	tests/test-sampling \
+	tests/test-tokenizer-0 \
+	tests/test-tokenizer-1-bpe \
+	tests/test-tokenizer-1-spm
 
 # Code coverage output files
 COV_TARGETS = *.gcno tests/*.gcno *.gcda tests/*.gcda *.gcov tests/*.gcov lcov-report gcovr-report
@@ -60,11 +72,17 @@ default: $(BUILD_TARGETS)
 test: $(TEST_TARGETS)
 	@failures=0; \
 	for test_target in $(TEST_TARGETS); do \
-		if [ "$$test_target" = "tests/test-tokenizer-0-llama" ]; then \
-			./$$test_target $(CURDIR)/models/ggml-vocab-llama.gguf; \
-		elif [ "$$test_target" = "tests/test-tokenizer-0-falcon" ]; then \
+		if [ "$$test_target" = "tests/test-tokenizer-0" ]; then \
+			./$$test_target $(CURDIR)/models/ggml-vocab-llama-spm.gguf; \
+			./$$test_target $(CURDIR)/models/ggml-vocab-llama-bpe.gguf; \
+			./$$test_target $(CURDIR)/models/ggml-vocab-phi-3.gguf; \
 			./$$test_target $(CURDIR)/models/ggml-vocab-falcon.gguf; \
-		elif [ "$$test_target" = "tests/test-tokenizer-1-llama" ]; then \
+			./$$test_target $(CURDIR)/models/ggml-vocab-deepseek-coder.gguf; \
+			./$$test_target $(CURDIR)/models/ggml-vocab-deepseek-llm.gguf; \
+			./$$test_target $(CURDIR)/models/ggml-vocab-bert-bge.gguf; \
+			./$$test_target $(CURDIR)/models/ggml-vocab-starcoder.gguf; \
+			./$$test_target $(CURDIR)/models/ggml-vocab-gpt-2.gguf; \
+		elif [ "$$test_target" = "tests/test-tokenizer-1-spm" ]; then \
 			continue; \
 		elif [ "$$test_target" = "tests/test-tokenizer-1-bpe" ]; then \
 			continue; \
@@ -982,11 +1000,7 @@ tests/test-sampling: tests/test-sampling.cpp ggml.o llama.o $(OBJS)
 	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
 	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
 
-tests/test-tokenizer-0-falcon: tests/test-tokenizer-0-falcon.cpp ggml.o llama.o $(COMMON_DEPS) console.o $(OBJS)
-	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
-	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
-
-tests/test-tokenizer-0-llama: tests/test-tokenizer-0-llama.cpp ggml.o llama.o $(COMMON_DEPS) console.o $(OBJS)
+tests/test-tokenizer-0: tests/test-tokenizer-0.cpp ggml.o llama.o $(COMMON_DEPS) console.o $(OBJS)
 	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
 	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
 
@@ -994,7 +1008,7 @@ tests/test-tokenizer-1-bpe: tests/test-tokenizer-1-bpe.cpp ggml.o llama.o $(COMM
 	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
 	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
 
-tests/test-tokenizer-1-llama: tests/test-tokenizer-1-llama.cpp ggml.o llama.o $(COMMON_DEPS) console.o $(OBJS)
+tests/test-tokenizer-1-spm: tests/test-tokenizer-1-spm.cpp ggml.o llama.o $(COMMON_DEPS) console.o $(OBJS)
 	$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
 	$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
 
diff --git a/common/common.cpp b/common/common.cpp
index d42fa131de3f64..aa494291dd52be 100644
--- a/common/common.cpp
+++ b/common/common.cpp
@@ -1693,6 +1693,18 @@ std::vector<std::string> string_split(std::string input, char separator) {
     return parts;
 }
 
+std::string string_strip(const std::string & str) {
+    size_t start = 0;
+    size_t end = str.size();
+    while (start < end && std::isspace(str[start])) {
+        start++;
+    }
+    while (end > start && std::isspace(str[end - 1])) {
+        end--;
+    }
+    return str.substr(start, end - start);
+}
+
 std::vector<llama_sampler_type> sampler_types_from_names(const std::vector<std::string> & names, bool allow_alt_names) {
     std::unordered_map<std::string, llama_sampler_type> sampler_canonical_name_map {
         {"top_k",       llama_sampler_type::TOP_K},
diff --git a/common/common.h b/common/common.h
index 96a28a6ce1b7fc..eea63a1142a4dd 100644
--- a/common/common.h
+++ b/common/common.h
@@ -196,6 +196,7 @@ bool validate_file_name(const std::string & filename);
 std::vector<llama_sampler_type> sampler_types_from_names(const std::vector<std::string> & names, bool allow_alt_names);
 std::vector<llama_sampler_type> sampler_types_from_chars(const std::string & names_string);
 std::vector<std::string> string_split(std::string input, char separator);
+std::string string_strip(const std::string & str);
 std::string sampler_type_to_name_string(llama_sampler_type sampler_type);
 
 //
diff --git a/convert-hf-to-gguf-update.py b/convert-hf-to-gguf-update.py
new file mode 100644
index 00000000000000..1c559c3f693be0
--- /dev/null
+++ b/convert-hf-to-gguf-update.py
@@ -0,0 +1,275 @@
+# This script downloads the tokenizer models of the specified models from Huggingface and
+# generates the get_vocab_base_pre() function for convert-hf-to-gguf.py
+#
+# This is necessary in order to analyze the type of pre-tokenizer used by the model and
+# provide the necessary information to llama.cpp via the GGUF header in order to implement
+# the same pre-tokenizer.
+#
+# ref: https://github.com/ggerganov/llama.cpp/pull/6920
+#
+# Instructions:
+#
+# - Add a new model to the "models" list
+# - Run the script with your huggingface token:
+#
+#   python3 convert-hf-to-gguf-update.py <huggingface_token>
+#
+# - Copy-paste the generated get_vocab_base_pre() function into convert-hf-to-gguf.py
+# - Update llama.cpp with the new pre-tokenizer if necessary
+#
+# TODO: generate tokenizer tests for llama.cpp
+# TODO: automate the update of convert-hf-to-gguf.py
+#
+
+import os
+import requests
+import sys
+import json
+
+from hashlib import sha256
+from enum import IntEnum, auto
+
+class TOKENIZER_TYPE(IntEnum):
+    SPM = auto()
+    BPE = auto()
+    WPM = auto()
+
+# TODO: this string has to exercise as much pre-tokenizer functionality as possible
+#       will be updated with time - contributions welcome
+chktxt = '\n \n\n \n\n\n \t \t\t \t\n  \n   \n    \n     \n🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天～ ------======= нещо на Български \'\'\'\'\'\'```````\"\"\"\"......!!!!!!?????? I\'ve been \'told he\'s there, \'RE you sure? \'M not sure I\'ll make it, \'D you like some tea? We\'Ve a\'lL'
+
+if len(sys.argv) == 2:
+    token = sys.argv[1]
+else:
+    print("Usage: python convert-hf-to-gguf-update.py <huggingface_token>")
+    sys.exit(1)
+
+# TODO: add models here, base models preferred
+models = [
+        { "name": "llama-spm",      "tokt": TOKENIZER_TYPE.SPM, "repo": "https://huggingface.co/meta-llama/Llama-2-7b-hf", },
+        { "name": "llama-bpe",      "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/meta-llama/Meta-Llama-3-8B", },
+        { "name": "phi-3",          "tokt": TOKENIZER_TYPE.SPM, "repo": "https://huggingface.co/microsoft/Phi-3-mini-4k-instruct", },
+        { "name": "deepseek-llm",   "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/deepseek-ai/deepseek-llm-7b-base", },
+        { "name": "deepseek-coder", "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-base", },
+        { "name": "falcon",         "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/tiiuae/falcon-7b", },
+        { "name": "bert-bge",       "tokt": TOKENIZER_TYPE.WPM, "repo": "https://huggingface.co/BAAI/bge-small-en-v1.5", },
+        { "name": "mpt",            "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/mosaicml/mpt-7b", },
+        { "name": "starcoder",      "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/bigcode/starcoder2-3b", },
+        { "name": "gpt-2",          "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/openai-community/gpt2", },
+        ]
+
+# make directory "models/tokenizers" if it doesn't exist
+if not os.path.exists("models/tokenizers"):
+    os.makedirs("models/tokenizers")
+
+def download_file_with_auth(url, token, save_path):
+    headers = {"Authorization": f"Bearer {token}"}
+    response = requests.get(url, headers=headers)
+    if response.status_code == 200:
+        with open(save_path, 'wb') as f:
+            f.write(response.content)
+        print(f"File {save_path} downloaded successfully")
+    else:
+        print(f"Failed to download file. Status code: {response.status_code}")
+
+# download the tokenizer models
+for model in models:
+    name = model["name"]
+    repo = model["repo"]
+    tokt = model["tokt"]
+
+    if not os.path.exists(f"models/tokenizers/{name}"):
+        os.makedirs(f"models/tokenizers/{name}")
+    else:
+        print(f"Directory models/tokenizers/{name} already exists - skipping")
+        continue
+
+    print(f"Downloading {name} to models/tokenizers/{name}")
+
+    url = f"{repo}/raw/main/config.json"
+    save_path = f"models/tokenizers/{name}/config.json"
+    download_file_with_auth(url, token, save_path)
+
+    url = f"{repo}/raw/main/tokenizer.json"
+    save_path = f"models/tokenizers/{name}/tokenizer.json"
+    download_file_with_auth(url, token, save_path)
+
+    if tokt == TOKENIZER_TYPE.SPM:
+        url = f"{repo}/resolve/main/tokenizer.model"
+        save_path = f"models/tokenizers/{name}/tokenizer.model"
+        download_file_with_auth(url, token, save_path)
+
+    url = f"{repo}/raw/main/tokenizer_config.json"
+    save_path = f"models/tokenizers/{name}/tokenizer_config.json"
+    download_file_with_auth(url, token, save_path)
+
+# generate the source code for the convert-hf-to-gguf.py:get_vocab_base_pre() function:
+# TODO: auto-update convert-hf-to-gguf.py with the generated function
+
+src_ifs = ""
+for model in models:
+    name = model["name"]
+    tokt = model["tokt"]
+
+    if tokt == TOKENIZER_TYPE.SPM:
+        continue
+
+    # create the tokenizer
+    from transformers import AutoTokenizer
+    tokenizer = AutoTokenizer.from_pretrained(f"models/tokenizers/{name}")
+
+    chktok = tokenizer.encode(chktxt)
+    chkhsh = sha256(str(chktok).encode()).hexdigest()
+
+    print(f"model: {name}")
+    print(f"tokt: {tokt}")
+    print(f"repo: {model['repo']}")
+    print(f"chktok: {chktok}")
+    print(f"chkhsh: {chkhsh}")
+
+    # print the "pre_tokenizer" content from the tokenizer.json
+    with open(f"models/tokenizers/{name}/tokenizer.json", "r") as f:
+        cfg = json.load(f)
+        pre_tokenizer = cfg["pre_tokenizer"]
+        print("pre_tokenizer: " + json.dumps(pre_tokenizer, indent=4))
+
+    print(f"\n")
+
+    src_ifs += f"        if chkhsh == \"{chkhsh}\":\n"
+    src_ifs += f"            # ref: {model['repo']}\n"
+    src_ifs += f"            res = \"{name}\"\n"
+
+src_func = ""
+src_func +=  "    def get_vocab_base_pre(self, tokenizer) -> str:\n"
+src_func +=  "        # encoding this string and hashing the resulting tokens would (hopefully) give us a unique identifier that\n"
+src_func +=  "        # is specific for the BPE pre-tokenizer used by the model\n"
+src_func +=  "        # we will use this unique identifier to write a \"tokenizer.ggml.pre\" entry in the GGUF file which we can\n"
+src_func +=  "        # use in llama.cpp to implement the same pre-tokenizer\n"
+src_func +=  "\n"
+src_func += f"        chktxt = {repr(chktxt)}\n"
+src_func +=  "\n"
+src_func +=  "        chktok = tokenizer.encode(chktxt)\n"
+src_func +=  "        chkhsh = sha256(str(chktok).encode()).hexdigest()\n"
+src_func +=  "\n"
+src_func +=  "        print(f\"chktok: {chktok}\")\n"
+src_func +=  "        print(f\"chkhsh: {chkhsh}\")\n"
+src_func +=  "\n"
+src_func +=  "        res = None\n"
+src_func +=  "\n"
+src_func +=  "        # NOTE: if you get an error here, you need to add the model to the if-elif chain below\n"
+src_func +=  "        #       don't do this manually - use the convert-hf-to-gguf-update.py script!\n"
+src_func += f"{src_ifs}\n"
+src_func +=  "        if res is None:\n"
+src_func +=  "            print(\"\\n\")\n"
+src_func +=  "            print(\"**************************************************************************************\")\n"
+src_func +=  "            print(\"** WARNING: The BPE pre-tokenizer was not recognized!\")\n"
+src_func +=  "            print(\"**          This means that it was not added yet or you are using an older version.\")\n"
+src_func +=  "            print(\"**          Check convert-hf-to-gguf-update.py and update it accordingly.\")\n"
+src_func +=  "            print(\"**\")\n"
+src_func +=  "            print(f\"** chkhsh:  {chkhsh}\")\n"
+src_func +=  "            print(\"**************************************************************************************\")\n"
+src_func +=  "            print(\"\\n\")\n"
+src_func +=  "            raise NotImplementedError(\"BPE pre-tokenizer was not recognized - update get_vocab_base_pre()\")\n"
+src_func +=  "\n"
+src_func +=  "        print(f\"tokenizer.ggml.pre: {res}\")\n"
+src_func +=  "        print(f\"chkhsh: {chkhsh}\")\n"
+src_func +=  "\n"
+src_func +=  "        return res\n"
+
+print(src_func)
+
+print("\n")
+print("!!! Copy-paste the function above into convert-hf-to-gguf.py !!!")
+print("\n")
+
+# generate tests for each tokenizer model
+
+tests = [
+    "",
+    " ",
+    "  ",
+    "   ",
+    "\t",
+    "\n",
+    "\n\n",
+    "\n\n\n",
+    "\t\n",
+    "Hello world",
+    " Hello world",
+    "Hello World",
+    " Hello World",
+    " Hello World!",
+    "Hello, world!",
+    " Hello, world!",
+    " this is 🦙.cpp",
+    "w048 7tuijk dsdfhu",
+    "нещо на Български",
+    "កាន់តែពិសេសអាចខលចេញ",
+    "🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)",
+    "Hello",
+    " Hello",
+    "  Hello",
+    "   Hello",
+    "    Hello",
+    "    Hello\n    Hello",
+    " (",
+    "\n =",
+    "' era",
+    "Hello, y'all! How are you 😁 ?我想在apple工作1314151天～",
+    "3",
+    "33",
+    "333",
+    "3333",
+    "33333",
+    "333333",
+    "3333333",
+    "33333333",
+    "333333333",
+    chktxt,
+]
+
+# write the tests to ./models/ggml-vocab-{name}.gguf.inp
+# the format is:
+#
+# test0
+# __ggml_vocab_test__
+# test1
+# __ggml_vocab_test__
+# ...
+#
+
+# with each model, encode all tests and write the results in ./models/ggml-vocab-{name}.gguf.out
+# for each test, write the resulting tokens on a separate line
+
+for model in models:
+    name = model["name"]
+    tokt = model["tokt"]
+
+    # create the tokenizer
+    from transformers import AutoTokenizer
+    tokenizer = AutoTokenizer.from_pretrained(f"models/tokenizers/{name}")
+
+    with open(f"models/ggml-vocab-{name}.gguf.inp", "w") as f:
+        for text in tests:
+            f.write(f"{text}")
+            f.write("\n__ggml_vocab_test__\n")
+
+    with open(f"models/ggml-vocab-{name}.gguf.out", "w") as f:
+        for text in tests:
+            res = tokenizer.encode(text, add_special_tokens=False)
+            for r in res:
+                f.write(f" {r}")
+            f.write("\n")
+
+    print(f"Tests for {name} written in ./models/ggml-vocab-{name}.gguf.*")
+
+# generate commands for creating vocab files
+
+print("\nRun the following commands to generate the vocab files for testing:\n")
+
+for model in models:
+    name = model["name"]
+
+    print(f"python3 convert-hf-to-gguf.py models/tokenizers/{name}/ --outfile models/ggml-vocab-{name}.gguf --vocab-only")
+
+print("\n")
diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py
index 30dc8229e75697..3cb6649c5e7e53 100755
--- a/convert-hf-to-gguf.py
+++ b/convert-hf-to-gguf.py
@@ -11,6 +11,7 @@
 from abc import ABC, abstractmethod
 from enum import IntEnum
 from pathlib import Path
+from hashlib import sha256
 from typing import TYPE_CHECKING, Any, Callable, ContextManager, Iterator, Sequence, TypeVar, cast
 
 import numpy as np
@@ -229,7 +230,7 @@ def _get_part_names(self):
         return (f"pytorch_model-{n:05}-of-{self.num_parts:05}.bin" for n in range(1, self.num_parts + 1))
 
     # used for GPT-2 BPE and WordPiece vocabs
-    def get_basic_vocab(self) -> tuple[list[str], list[int]]:
+    def get_vocab_base(self) -> tuple[list[str], list[int], str]:
         tokens: list[str] = []
         toktypes: list[int] = []
 
@@ -238,6 +239,8 @@ def get_basic_vocab(self) -> tuple[list[str], list[int]]:
         vocab_size = self.hparams.get("vocab_size", len(tokenizer.vocab))
         assert max(tokenizer.vocab.values()) < vocab_size
 
+        tokpre = self.get_vocab_base_pre(tokenizer)
+
         reverse_vocab = {id_: encoded_tok for encoded_tok, id_ in tokenizer.vocab.items()}
         added_vocab = tokenizer.get_added_vocab()
 
@@ -255,11 +258,75 @@ def get_basic_vocab(self) -> tuple[list[str], list[int]]:
                 tokens.append(reverse_vocab[i])
                 toktypes.append(gguf.TokenType.NORMAL)
 
-        return tokens, toktypes
+        return tokens, toktypes, tokpre
+
+    # NOTE: this function is generated by convert-hf-to-gguf-update.py
+    #       do not modify it manually!
+    # ref:  https://github.com/ggerganov/llama.cpp/pull/6920
+    def get_vocab_base_pre(self, tokenizer) -> str:
+        # encoding this string and hashing the resulting tokens would (hopefully) give us a unique identifier that
+        # is specific for the BPE pre-tokenizer used by the model
+        # we will use this unique identifier to write a "tokenizer.ggml.pre" entry in the GGUF file which we can
+        # use in llama.cpp to implement the same pre-tokenizer
+
+        chktxt = '\n \n\n \n\n\n \t \t\t \t\n  \n   \n    \n     \n🚀 (normal) 😶\u200d🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天～ ------======= нещо на Български \'\'\'\'\'\'```````""""......!!!!!!?????? I\'ve been \'told he\'s there, \'RE you sure? \'M not sure I\'ll make it, \'D you like some tea? We\'Ve a\'lL'
+
+        chktok = tokenizer.encode(chktxt)
+        chkhsh = sha256(str(chktok).encode()).hexdigest()
+
+        print(f"chktok: {chktok}")
+        print(f"chkhsh: {chkhsh}")
+
+        res = None
+
+        # NOTE: if you get an error here, you need to add the model to the if-elif chain below
+        #       don't do this manually - use the convert-hf-to-gguf-update.py script!
+        if chkhsh == "0ef9807a4087ebef797fc749390439009c3b9eda9ad1a097abbe738f486c01e5":
+            # ref: https://huggingface.co/meta-llama/Meta-Llama-3-8B
+            res = "llama-bpe"
+        if chkhsh == "049ecf7629871e3041641907f3de7c733e4dbfdc736f57d882ba0b0845599754":
+            # ref: https://huggingface.co/deepseek-ai/deepseek-llm-7b-base
+            res = "deepseek-llm"
+        if chkhsh == "347715f544604f9118bb75ed199f68779f423cabb20db6de6f31b908d04d7821":
+            # ref: https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-base
+            res = "deepseek-coder"
+        if chkhsh == "8aeee3860c56296a157a1fe2fad249ec40aa59b1bb5709f4ade11c4e6fe652ed":
+            # ref: https://huggingface.co/tiiuae/falcon-7b
+            res = "falcon"
+        if chkhsh == "0876d13b50744004aa9aeae05e7b0647eac9d801b5ba4668afc01e709c15e19f":
+            # ref: https://huggingface.co/BAAI/bge-small-en-v1.5
+            res = "bert-bge"
+        if chkhsh == "b6dc8df998e1cfbdc4eac8243701a65afe638679230920b50d6f17d81c098166":
+            # ref: https://huggingface.co/mosaicml/mpt-7b
+            res = "mpt"
+        if chkhsh == "35d91631860c815f952d711435f48d356ebac988362536bed955d43bfa436e34":
+            # ref: https://huggingface.co/bigcode/starcoder2-3b
+            res = "starcoder"
+        if chkhsh == "3ce83efda5659b07b1ad37ca97ca5797ea4285d9b9ab0dc679e4a720c9da7454":
+            # ref: https://huggingface.co/openai-community/gpt2
+            res = "gpt-2"
+
+        if res is None:
+            print("\n")
+            print("**************************************************************************************")
+            print("** WARNING: The BPE pre-tokenizer was not recognized!")
+            print("**          This means that it was not added yet or you are using an older version.")
+            print("**          Check convert-hf-to-gguf-update.py and update it accordingly.")
+            print("**")
+            print(f"** chkhsh:  {chkhsh}")
+            print("**************************************************************************************")
+            print("\n")
+            raise NotImplementedError("BPE pre-tokenizer was not recognized - update get_vocab_base_pre()")
+
+        print(f"tokenizer.ggml.pre: {res}")
+        print(f"chkhsh: {chkhsh}")
+
+        return res
 
     def _set_vocab_gpt2(self) -> None:
-        tokens, toktypes = self.get_basic_vocab()
+        tokens, toktypes, tokpre = self.get_vocab_base()
         self.gguf_writer.add_tokenizer_model("gpt2")
+        self.gguf_writer.add_tokenizer_pre(tokpre)
         self.gguf_writer.add_token_list(tokens)
         self.gguf_writer.add_token_types(toktypes)
 
@@ -277,6 +344,8 @@ def _set_vocab_qwen(self):
         vocab_size = hparams["vocab_size"]
         assert max(tokenizer.get_vocab().values()) < vocab_size
 
+        tokpre = self.get_vocab_base_pre(tokenizer)
+
         merges = []
         vocab = {}
         mergeable_ranks = tokenizer.mergeable_ranks
@@ -304,6 +373,7 @@ def _set_vocab_qwen(self):
                 toktypes.append(gguf.TokenType.NORMAL)
 
         self.gguf_writer.add_tokenizer_model("gpt2")
+        self.gguf_writer.add_tokenizer_pre(tokpre)
         self.gguf_writer.add_token_list(tokens)
         self.gguf_writer.add_token_types(toktypes)
 
@@ -376,6 +446,7 @@ def _set_vocab_sentencepiece(self):
         assert len(tokens) == vocab_size
 
         self.gguf_writer.add_tokenizer_model("llama")
+        self.gguf_writer.add_tokenizer_pre("default")
         self.gguf_writer.add_token_list(tokens)
         self.gguf_writer.add_token_scores(scores)
         self.gguf_writer.add_token_types(toktypes)
@@ -397,6 +468,7 @@ def _set_vocab_llama_hf(self):
         assert len(tokens) == vocab.vocab_size
 
         self.gguf_writer.add_tokenizer_model("llama")
+        self.gguf_writer.add_tokenizer_pre("default")
         self.gguf_writer.add_token_list(tokens)
         self.gguf_writer.add_token_scores(scores)
         self.gguf_writer.add_token_types(toktypes)
@@ -840,6 +912,7 @@ def set_vocab(self):
             toktypes.append(toktype)
 
         self.gguf_writer.add_tokenizer_model("llama")
+        self.gguf_writer.add_tokenizer_pre("default")
         self.gguf_writer.add_token_list(tokens)
         self.gguf_writer.add_token_types(toktypes)
 
@@ -1335,6 +1408,11 @@ def set_gguf_parameters(self):
         self.gguf_writer.add_vocab_size(hparams["vocab_size"])
         self.gguf_writer.add_rope_dimension_count(hparams["hidden_size"] // hparams["num_attention_heads"])
 
+        if self.hparams.get("rope_scaling") is not None and "factor" in self.hparams["rope_scaling"]:
+            if self.hparams["rope_scaling"].get("type") == "linear":
+                self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.LINEAR)
+                self.gguf_writer.add_rope_scaling_factor(self.hparams["rope_scaling"]["factor"])
+
     # Same as super class, but permuting q_proj, k_proj
     def write_tensors(self):
         block_count = self.hparams.get("n_layers", self.hparams.get("num_hidden_layers", self.hparams.get("n_layer")))
@@ -2052,6 +2130,7 @@ def set_vocab(self):
                     toktypes[token_id] = SentencePieceTokenTypes.USER_DEFINED
 
         self.gguf_writer.add_tokenizer_model("llama")
+        self.gguf_writer.add_tokenizer_pre("default")
         self.gguf_writer.add_token_list(tokens)
         self.gguf_writer.add_token_scores(scores)
         self.gguf_writer.add_token_types(toktypes)
@@ -2294,6 +2373,7 @@ def set_vocab(self):
                     toktypes.append(SentencePieceTokenTypes.USER_DEFINED)
 
         self.gguf_writer.add_tokenizer_model("llama")
+        self.gguf_writer.add_tokenizer_pre("default")
         self.gguf_writer.add_token_list(tokens)
         self.gguf_writer.add_token_scores(scores)
         self.gguf_writer.add_token_types(toktypes)
@@ -2443,7 +2523,7 @@ def set_gguf_parameters(self):
             self.gguf_writer.add_pooling_type(pooling_type)
 
     def set_vocab(self):
-        tokens, toktypes = self.get_basic_vocab()
+        tokens, toktypes, tokpre = self.get_vocab_base()
         self.vocab_size = len(tokens)
 
         # we need this to validate the size of the token_type embeddings
@@ -2461,6 +2541,7 @@ def phantom(tok):
 
         # add vocab to gguf
         self.gguf_writer.add_tokenizer_model("bert")
+        self.gguf_writer.add_tokenizer_pre(tokpre)
         self.gguf_writer.add_token_list(tokens)
         self.gguf_writer.add_token_types(toktypes)
 
@@ -2642,6 +2723,9 @@ def set_vocab(self):
             field = neox_reader.get_field(gguf.Keys.Tokenizer.MODEL)
             self.gguf_writer.add_tokenizer_model(bytes(field.parts[-1]))
 
+            field = neox_reader.get_field(gguf.Keys.Tokenizer.PRE)
+            self.gguf_writer.add_tokenizer_pre(bytes(field.parts[-1]))
+
             field = neox_reader.get_field(gguf.Keys.Tokenizer.LIST)
             self.gguf_writer.add_token_list([bytes(field.parts[i]) for i in field.data][:vocab_size])
 
@@ -2848,6 +2932,7 @@ def parse_args() -> argparse.Namespace:
         help="directory containing model file",
     )
     parser.add_argument("--use-temp-file", action="store_true", help="use the tempfile library while processing (helpful when running out of memory, process killed)")
+    parser.add_argument("--model-name", type=str, default=None, help="name of the model")
 
     return parser.parse_args()
 
diff --git a/convert-llama-ggml-to-gguf.py b/convert-llama-ggml-to-gguf.py
index cd9644fcb52133..5354b748b259f5 100755
--- a/convert-llama-ggml-to-gguf.py
+++ b/convert-llama-ggml-to-gguf.py
@@ -281,6 +281,7 @@ def add_params(self, gguf_writer):
     def add_vocab(self, gguf_writer):
         hp = self.model.hyperparameters
         gguf_writer.add_tokenizer_model('llama')
+        gguf_writer.add_tokenizer_pre('default')
         tokens = []
         scores = []
         toktypes = []
diff --git a/convert-persimmon-to-gguf.py b/convert-persimmon-to-gguf.py
index 69be17f94efd9d..aba575426b4929 100755
--- a/convert-persimmon-to-gguf.py
+++ b/convert-persimmon-to-gguf.py
@@ -99,6 +99,7 @@ def main():
 
     tokens, scores, toktypes = _get_sentencepiece_tokenizer_info(args.model_dir)
     gguf_writer.add_tokenizer_model('llama')
+    gguf_writer.add_tokenizer_pre('default')
     gguf_writer.add_token_list(tokens)
     gguf_writer.add_token_scores(scores)
     gguf_writer.add_token_types(toktypes)
diff --git a/gguf-py/gguf/constants.py b/gguf-py/gguf/constants.py
index d2f1de19831e34..6d597bfd9d621a 100644
--- a/gguf-py/gguf/constants.py
+++ b/gguf-py/gguf/constants.py
@@ -72,6 +72,7 @@ class SSM:
 
     class Tokenizer:
         MODEL            = "tokenizer.ggml.model"
+        PRE              = "tokenizer.ggml.pre"
         LIST             = "tokenizer.ggml.tokens"
         TOKEN_TYPE       = "tokenizer.ggml.token_type"
         TOKEN_TYPE_COUNT = "tokenizer.ggml.token_type_count"  # for BERT-style token types
@@ -940,6 +941,7 @@ def get_type(val: Any) -> GGUFValueType:
 
 # tokenization
 KEY_TOKENIZER_MODEL      = Keys.Tokenizer.MODEL
+KEY_TOKENIZER_PRE        = Keys.Tokenizer.PRE
 KEY_TOKENIZER_LIST       = Keys.Tokenizer.LIST
 KEY_TOKENIZER_TOKEN_TYPE = Keys.Tokenizer.TOKEN_TYPE
 KEY_TOKENIZER_SCORES     = Keys.Tokenizer.SCORES
diff --git a/gguf-py/gguf/gguf_reader.py b/gguf-py/gguf/gguf_reader.py
index 48ef6d4ae45dfa..2bdb15525b1a13 100644
--- a/gguf-py/gguf/gguf_reader.py
+++ b/gguf-py/gguf/gguf_reader.py
@@ -139,8 +139,13 @@ def _get(
 
     def _push_field(self, field: ReaderField, skip_sum: bool = False) -> int:
         if field.name in self.fields:
-            raise KeyError(f'Duplicate {field.name} already in list at offset {field.offset}')
-        self.fields[field.name] = field
+            # TODO: add option to generate error on duplicate keys
+            # raise KeyError(f'Duplicate {field.name} already in list at offset {field.offset}')
+
+            print(f'Warning: Duplicate key {field.name} at offset {field.offset}')
+            self.fields[field.name + '_{}'.format(field.offset)] = field
+        else:
+            self.fields[field.name] = field
         return 0 if skip_sum else sum(int(part.nbytes) for part in field.parts)
 
     def _get_str(self, offset: int) -> tuple[npt.NDArray[np.uint64], npt.NDArray[np.uint8]]:
diff --git a/gguf-py/gguf/gguf_writer.py b/gguf-py/gguf/gguf_writer.py
index ec44ac9f3813dd..089aece876a93d 100644
--- a/gguf-py/gguf/gguf_writer.py
+++ b/gguf-py/gguf/gguf_writer.py
@@ -427,6 +427,9 @@ def add_ssm_time_step_rank(self, value: int) -> None:
     def add_tokenizer_model(self, model: str) -> None:
         self.add_string(Keys.Tokenizer.MODEL, model)
 
+    def add_tokenizer_pre(self, pre: str) -> None:
+        self.add_string(Keys.Tokenizer.PRE, pre)
+
     def add_token_list(self, tokens: Sequence[str] | Sequence[bytes] | Sequence[bytearray]) -> None:
         self.add_array(Keys.Tokenizer.LIST, tokens)
 
diff --git a/llama.cpp b/llama.cpp
index 30af5991fe8f01..72c10ffc202fcc 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -317,6 +317,7 @@ enum llm_kv {
     LLM_KV_SSM_TIME_STEP_RANK,
 
     LLM_KV_TOKENIZER_MODEL,
+    LLM_KV_TOKENIZER_PRE,
     LLM_KV_TOKENIZER_LIST,
     LLM_KV_TOKENIZER_TOKEN_TYPE,
     LLM_KV_TOKENIZER_TOKEN_TYPE_COUNT,
@@ -393,6 +394,7 @@ static const std::map<llm_kv, const char *> LLM_KV_NAMES = {
     { LLM_KV_SSM_TIME_STEP_RANK,            "%s.ssm.time_step_rank" },
 
     { LLM_KV_TOKENIZER_MODEL,               "tokenizer.ggml.model"              },
+    { LLM_KV_TOKENIZER_PRE,                 "tokenizer.ggml.pre"                },
     { LLM_KV_TOKENIZER_LIST,                "tokenizer.ggml.tokens"             },
     { LLM_KV_TOKENIZER_TOKEN_TYPE,          "tokenizer.ggml.token_type"         },
     { LLM_KV_TOKENIZER_TOKEN_TYPE_COUNT,    "tokenizer.ggml.token_type_count"   },
@@ -2115,7 +2117,8 @@ struct llama_vocab {
         ttype type;
     };
 
-    enum llama_vocab_type type = LLAMA_VOCAB_TYPE_SPM;
+    enum llama_vocab_type     type     = LLAMA_VOCAB_TYPE_SPM;
+    enum llama_vocab_pre_type type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
 
     std::unordered_map<token, id> token_to_id;
     std::vector<token_data>       id_to_token;
@@ -4214,11 +4217,13 @@ static void llm_load_vocab(
 
     // determine vocab type
     {
-        std::string tokenizer_name;
+        std::string tokenizer_model;
+        std::string tokenizer_pre;
 
-        ml.get_key(LLM_KV_TOKENIZER_MODEL, tokenizer_name);
+        ml.get_key(LLM_KV_TOKENIZER_MODEL, tokenizer_model);
+        ml.get_key(LLM_KV_TOKENIZER_PRE,   tokenizer_pre, false);
 
-        if (tokenizer_name == "no_vocab") {
+        if (tokenizer_model == "no_vocab") {
             vocab.type = LLAMA_VOCAB_TYPE_NONE;
 
             // default special tokens
@@ -4232,7 +4237,7 @@ static void llm_load_vocab(
             vocab.linefeed_id     = -1;
 
             return;
-        } else if (tokenizer_name == "llama") {
+        } else if (tokenizer_model == "llama") {
             vocab.type = LLAMA_VOCAB_TYPE_SPM;
 
             // default special tokens
@@ -4277,9 +4282,27 @@ static void llm_load_vocab(
             if (add_space_prefix_keyidx != -1) {
                 vocab.add_space_prefix = gguf_get_val_bool(ctx, add_space_prefix_keyidx);
             } // The default value of add_space_prefix is true.
-        } else if (tokenizer_name == "gpt2") {
-            vocab.type = LLAMA_VOCAB_TYPE_BPE;
+        } else if (tokenizer_model == "bert") {
+            vocab.type = LLAMA_VOCAB_TYPE_WPM;
 
+            // default special tokens
+            vocab.special_bos_id  = -1;
+            vocab.special_eos_id  = -1;
+            vocab.special_unk_id  = 100;
+            vocab.special_sep_id  = 102;
+            vocab.special_pad_id  = 0;
+            vocab.special_cls_id  = 101;
+            vocab.special_mask_id = 103;
+            vocab.add_space_prefix = false;
+        } else {
+            if (tokenizer_model == "gpt2") {
+                vocab.type = LLAMA_VOCAB_TYPE_BPE;
+            } else {
+                LLAMA_LOG_WARN("%s: unknown tokenizer: '%s'", __func__, tokenizer_model.c_str());
+                LLAMA_LOG_WARN("%s: using default tokenizer: 'llama'", __func__);
+                vocab.type = LLAMA_VOCAB_TYPE_SPM;
+                return;
+            }
             // read bpe merges and populate bpe ranks
             const int merges_keyidx = gguf_find_key(ctx, kv(LLM_KV_TOKENIZER_MERGES).c_str());
             if (merges_keyidx == -1) {
@@ -4313,23 +4336,50 @@ static void llm_load_vocab(
             vocab.special_pad_id  = -1;
             vocab.special_cls_id  = -1;
             vocab.special_mask_id = -1;
-        } else if (tokenizer_name == "bert") {
-            vocab.type = LLAMA_VOCAB_TYPE_WPM;
+        }
 
-            // default special tokens
-            vocab.special_bos_id  = -1;
-            vocab.special_eos_id  = -1;
-            vocab.special_unk_id  = 100;
-            vocab.special_sep_id  = 102;
-            vocab.special_pad_id  = 0;
-            vocab.special_cls_id  = 101;
-            vocab.special_mask_id = 103;
-            vocab.add_space_prefix = false;
+        // for now, only BPE models have pre-tokenizers
+        if (vocab.type == LLAMA_VOCAB_TYPE_BPE) {
+            if (tokenizer_pre.empty()) {
+                LLAMA_LOG_WARN("%s: missing pre-tokenizer type, using: 'default'\n", __func__);
+                LLAMA_LOG_WARN("%s:                                             \n", __func__);
+                LLAMA_LOG_WARN("%s: ************************************        \n", __func__);
+                LLAMA_LOG_WARN("%s: GENERATION QUALITY WILL BE DEGRADED!        \n", __func__);
+                LLAMA_LOG_WARN("%s: CONSIDER REGENERATING THE MODEL             \n", __func__);
+                LLAMA_LOG_WARN("%s: ************************************        \n", __func__);
+                LLAMA_LOG_WARN("%s:                                             \n", __func__);
+                vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
+            } else if (
+                    tokenizer_pre == "default") {
+                vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
+            } else if (
+                    tokenizer_pre == "llama3"   ||
+                    tokenizer_pre == "llama-v3" ||
+                    tokenizer_pre == "llama-bpe") {
+                vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_LLAMA3;
+            } else if (
+                    tokenizer_pre == "deepseek-llm") {
+                vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEEPSEEK_LLM;
+            } else if (
+                    tokenizer_pre == "deepseek-coder") {
+                vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEEPSEEK_CODER;
+            } else if (
+                    tokenizer_pre == "falcon") {
+                vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_FALCON;
+            } else if (
+                    tokenizer_pre == "mpt") {
+                vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_MPT;
+            } else if (
+                    tokenizer_pre == "starcoder") {
+                vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_STARCODER;
+            } else if (
+                    tokenizer_pre == "gpt-2") {
+                vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_GPT2;
+            } else {
+                throw std::runtime_error(format("unknown pre-tokenizer type: '%s'", tokenizer_pre.c_str()));
+            }
         } else {
-            LLAMA_LOG_WARN("%s: unknown tokenizer: '%s'", __func__, tokenizer_name.c_str());
-            LLAMA_LOG_WARN("%s: using default tokenizer: 'llama'", __func__);
-
-            vocab.type = LLAMA_VOCAB_TYPE_SPM;
+            vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
         }
     }
 
@@ -11834,7 +11884,7 @@ static uint8_t llama_token_to_byte(const llama_vocab& vocab, llama_token id) {
         }
         case LLAMA_VOCAB_TYPE_BPE: {
             GGML_ASSERT(false);
-            return unicode_utf8_to_byte(token_data.text);
+            return unicode_utf8_to_byte(token_data.text); // TODO: why is this here after GGML_ASSERT?
         }
         case LLAMA_VOCAB_TYPE_WPM: {
             GGML_ASSERT(false);
@@ -12056,7 +12106,79 @@ struct llm_tokenizer_bpe {
 
     void tokenize(const std::string & text, std::vector<llama_vocab::id> & output) {
         int final_prev_index = -1;
-        auto word_collection = bpe_gpt2_preprocess(text);
+
+        std::vector<std::string> word_collection;
+        switch (vocab.type) {
+            case LLAMA_VOCAB_TYPE_BPE:
+                switch (vocab.type_pre) {
+                    case LLAMA_VOCAB_PRE_TYPE_LLAMA3:
+                        word_collection = unicode_regex_split(text, {
+                            // original regex from tokenizer.json
+                            //"(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
+
+                            // adapted: https://github.com/ggerganov/llama.cpp/pull/6920#issuecomment-2080233989
+                            "(?:'[sS]|'[tT]|'[rR][eE]|'[vV][eE]|'[mM]|'[lL][lL]|'[dD])|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
+                        });
+                        break;
+                    case LLAMA_VOCAB_PRE_TYPE_DEEPSEEK_LLM:
+                        word_collection = unicode_regex_split(text, {
+                            "[\r\n]",
+                            "\\s?[A-Za-zµÀ-ÖØ-öø-ƺƼ-ƿDŽ-ʓʕ-ʯͰ-ͳͶͷͻ-ͽͿΆΈ-ΊΌΎ-ΡΣ-ϵϷ-ҁҊ-ԯԱ-ՖႠ-ჅᎠ-Ᏽᏸ-ᏽᲐ-ᲺᲽ-Ჿᴀ-ᴫᵫ-ᵷᵹ-ᶚḀ-ἕἘ-Ἕἠ-ὅὈ-Ὅὐ-ὗὙὛὝὟ-ώᾀ-ᾴᾶ-ᾼιῂ-ῄῆ-ῌῐ-ΐῖ-Ίῠ-Ῥῲ-ῴῶ-ῼℂℇℊ-ℓℕℙ-ℝℤΩℨK-ℭℯ-ℴℹℼ-ℿⅅ-ⅉⅎↃↄⰀ-ⱻⱾ-ⳤⳫ-ⳮⳲⳳꙀ-ꙭꚀ-ꚛꜢ-ꝯꝱ-ꞇꞋ-ꞎꭰ-ꮿff-stﬓ-ﬗＡ-Ｚａ-ｚ𐐀-𐑏𐒰-𐓓𐓘-𐓻𐲀-𐲲𐳀-𐳲𑢠-𑣟𞤀-𞥃]+",
+                            "\\s?[!-/:-~！-／：-～‘-‟　-。]+",
+                            "\\s+$",
+                            "[一-龥ࠀ-一가-퟿]+",
+                            "\\p{N}+",
+                        });
+                        break;
+                    case LLAMA_VOCAB_PRE_TYPE_DEEPSEEK_CODER:
+                        word_collection = unicode_regex_split(text, {
+                            "[\r\n]",
+                            "\\s?\\p{L}+",
+                            "\\s?\\p{P}+",
+                            "[一-龥ࠀ-一가-퟿]+",
+                            "\\p{N}+",
+                        });
+                        break;
+                    case LLAMA_VOCAB_PRE_TYPE_FALCON:
+                        word_collection = unicode_regex_split(text, {
+                            "[\\p{P}\\$\\+<=>\\^~\\|]+",
+                            "'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)",
+                            "\\p{N}+",
+                            "[0-9][0-9][0-9]",
+                        });
+                        break;
+                    case LLAMA_VOCAB_PRE_TYPE_MPT:
+                        // TODO: MPT pre-tokenization regexes are unknown
+                        //       the following are close, but not exact. run the following:
+                        //       ./bin/test-tokenizer-0 ../models/ggml-vocab-mpt.gguf
+                        GGML_ASSERT("MPT pre-tokenization regexes are unknown - fixes needed");
+                        word_collection = unicode_regex_split(text, {
+                            "\\s?\\p{L}+",
+                            "\\s?\\p{P}+",
+                            "'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)",
+                        });
+                        break;
+                    case LLAMA_VOCAB_PRE_TYPE_STARCODER:
+                    case LLAMA_VOCAB_PRE_TYPE_GPT2:
+                        word_collection = unicode_regex_split(text, {
+                            "'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)",
+                        });
+                        break;
+                    default:
+                        // default regex for BPE tokenization pre-processing
+                        word_collection = unicode_regex_split(text, {
+                            "[\\p{P}\\$\\+<=>\\^~\\|]+",
+                            "'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)",
+                            "\\p{N}+",
+                            "[0-9][0-9][0-9]",
+                        });
+                        break;
+                }
+                break;
+            default:
+                GGML_ASSERT(false);
+                break;
+        }
 
         symbols_final.clear();
 
@@ -12183,145 +12305,6 @@ struct llm_tokenizer_bpe {
         work_queue.push(bigram);
     }
 
-    std::vector<std::string> bpe_gpt2_preprocess(const std::string & text) {
-        std::vector<std::string> bpe_words;
-        std::vector<std::string> bpe_encoded_words;
-
-        std::string token = "";
-        // GPT2 system regex:  's|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+
-        bool collecting_numeric = false;
-        bool collecting_letter = false;
-        bool collecting_special = false;
-        bool collecting_whitespace_lookahead = false;
-        bool collecting = false;
-
-        std::vector<std::string> text_utf;
-        text_utf.reserve(text.size());
-        bpe_words.reserve(text.size());
-        bpe_encoded_words.reserve(text.size());
-
-        const auto cpts = unicode_cpts_from_utf8(text);
-        for (size_t i = 0; i < cpts.size(); ++i)
-            text_utf.emplace_back(unicode_cpt_to_utf8(cpts[i]));
-
-        for (int i = 0; i < (int)text_utf.size(); i++) {
-            const std::string & utf_char = text_utf[i];
-            bool split_condition = false;
-            int bytes_remain = text_utf.size() - i;
-            // forward backward lookups
-            const std::string & utf_char_next = (i + 1 < (int)text_utf.size()) ? text_utf[i + 1] : "";
-            const std::string & utf_char_next_next = (i + 2 < (int)text_utf.size()) ? text_utf[i + 2] : "";
-
-            // handling contractions
-            if (!split_condition && bytes_remain >= 2) {
-                // 's|'t|'m|'d
-                if (utf_char == "\'" && (utf_char_next == "s" || utf_char_next == "t" || utf_char_next == "m" || utf_char_next == "d")) {
-                    split_condition = true;
-                }
-                if (split_condition) {
-                    if (token.size()) {
-                        bpe_words.emplace_back(token); // push previous content as token
-                    }
-                    token = utf_char + utf_char_next;
-                    bpe_words.emplace_back(token);
-                    token = "";
-                    i++;
-                    continue;
-                }
-            }
-            if (!split_condition && bytes_remain >= 3) {
-                // 're|'ve|'ll
-                if (utf_char == "\'" && (
-                    (utf_char_next == "r" && utf_char_next_next == "e") ||
-                    (utf_char_next == "v" && utf_char_next_next == "e") ||
-                    (utf_char_next == "l" && utf_char_next_next == "l"))
-                    ) {
-                    split_condition = true;
-                }
-                if (split_condition) {
-                    // current token + next token can be defined
-                    if (token.size()) {
-                        bpe_words.emplace_back(token); // push previous content as token
-                    }
-                    token = utf_char + utf_char_next + utf_char_next_next;
-                    bpe_words.emplace_back(token); // the contraction
-                    token = "";
-                    i += 2;
-                    continue;
-                }
-            }
-
-            if (!split_condition && !collecting) {
-                if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_LETTER || (!token.size() && utf_char == " " && unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_LETTER)) {
-                    collecting_letter = true;
-                    collecting = true;
-                }
-                else if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_DIGIT || (!token.size() && utf_char == " " && unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_DIGIT)) {
-                    collecting_numeric = true;
-                    collecting = true;
-                }
-                else if (
-                    ((unicode_cpt_type(utf_char) != CODEPOINT_TYPE_LETTER && unicode_cpt_type(utf_char) != CODEPOINT_TYPE_DIGIT) && (unicode_cpt_type(utf_char) != CODEPOINT_TYPE_WHITESPACE)) ||
-                    (!token.size() && utf_char == " " && unicode_cpt_type(utf_char_next) != CODEPOINT_TYPE_LETTER && unicode_cpt_type(utf_char_next) != CODEPOINT_TYPE_DIGIT && unicode_cpt_type(utf_char_next) != CODEPOINT_TYPE_WHITESPACE)
-                    ) {
-                    collecting_special = true;
-                    collecting = true;
-                }
-                else if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_WHITESPACE && unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_WHITESPACE) {
-                    collecting_whitespace_lookahead = true;
-                    collecting = true;
-                }
-                else if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_WHITESPACE) {
-                    split_condition = true;
-                }
-            }
-            else if (!split_condition && collecting) {
-                if (collecting_letter && unicode_cpt_type(utf_char) != CODEPOINT_TYPE_LETTER) {
-                    split_condition = true;
-                }
-                else if (collecting_numeric && unicode_cpt_type(utf_char) != CODEPOINT_TYPE_DIGIT) {
-                    split_condition = true;
-                }
-                else if (collecting_special && (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_LETTER || unicode_cpt_type(utf_char) == CODEPOINT_TYPE_DIGIT || unicode_cpt_type(utf_char) == CODEPOINT_TYPE_WHITESPACE)) {
-                    split_condition = true;
-                }
-                else if (collecting_whitespace_lookahead && (unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_LETTER || unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_DIGIT)) {
-                    split_condition = true;
-                }
-            }
-
-            if (utf_char_next == "") {
-                split_condition = true; // final
-                token += utf_char;
-            }
-
-            if (split_condition) {
-                if (token.size()) {
-                    bpe_words.emplace_back(token);
-                }
-                token = utf_char;
-                collecting = false;
-                collecting_letter = false;
-                collecting_numeric = false;
-                collecting_special = false;
-                collecting_whitespace_lookahead = false;
-            }
-            else {
-                token += utf_char;
-            }
-        }
-
-        for (std::string & word : bpe_words) {
-            std::string encoded_token = "";
-            for (char & c : word) {
-                encoded_token += unicode_byte_to_utf8(c);
-            }
-            bpe_encoded_words.emplace_back(encoded_token);
-        }
-
-        return bpe_encoded_words;
-    }
-
     const llama_vocab & vocab;
 
     std::vector<llm_symbol> symbols;
@@ -12641,7 +12624,7 @@ static std::vector<llama_vocab::id> llama_tokenize_internal(const llama_vocab &
             } break;
         case LLAMA_VOCAB_TYPE_BPE:
             {
-                if (add_special && vocab.special_add_bos == 1) {
+                if (add_special && vocab.special_add_bos != 0) {
                     GGML_ASSERT(vocab.special_bos_id != -1);
                     output.push_back(vocab.special_bos_id);
                 }
diff --git a/llama.h b/llama.h
index 8b1b15ed4ad555..30835de5f9433e 100644
--- a/llama.h
+++ b/llama.h
@@ -69,6 +69,18 @@ extern "C" {
         LLAMA_VOCAB_TYPE_WPM  = 3, // BERT tokenizer based on WordPiece
     };
 
+    // pre-tokenization types
+    enum llama_vocab_pre_type {
+        LLAMA_VOCAB_PRE_TYPE_DEFAULT        = 0,
+        LLAMA_VOCAB_PRE_TYPE_LLAMA3         = 1,
+        LLAMA_VOCAB_PRE_TYPE_DEEPSEEK_LLM   = 2,
+        LLAMA_VOCAB_PRE_TYPE_DEEPSEEK_CODER = 3,
+        LLAMA_VOCAB_PRE_TYPE_FALCON         = 4,
+        LLAMA_VOCAB_PRE_TYPE_MPT            = 5,
+        LLAMA_VOCAB_PRE_TYPE_STARCODER      = 6,
+        LLAMA_VOCAB_PRE_TYPE_GPT2           = 7,
+    };
+
     // note: these values should be synchronized with ggml_rope
     // TODO: maybe move this enum to ggml.h (ggml_rope_type)
     enum llama_rope_type {
diff --git a/models/ggml-vocab-bert-bge.gguf b/models/ggml-vocab-bert-bge.gguf
new file mode 100644
index 00000000000000..b2cbd5df6882d8
Binary files /dev/null and b/models/ggml-vocab-bert-bge.gguf differ
diff --git a/models/ggml-vocab-bert-bge.gguf.inp b/models/ggml-vocab-bert-bge.gguf.inp
new file mode 100644
index 00000000000000..0389f00c713792
--- /dev/null
+++ b/models/ggml-vocab-bert-bge.gguf.inp
@@ -0,0 +1,102 @@
+
+__ggml_vocab_test__
+ 
+__ggml_vocab_test__
+  
+__ggml_vocab_test__
+   
+__ggml_vocab_test__
+	
+__ggml_vocab_test__
+
+
+__ggml_vocab_test__
+
+
+
+__ggml_vocab_test__
+
+
+
+
+__ggml_vocab_test__
+	
+
+__ggml_vocab_test__
+Hello world
+__ggml_vocab_test__
+ Hello world
+__ggml_vocab_test__
+Hello World
+__ggml_vocab_test__
+ Hello World
+__ggml_vocab_test__
+ Hello World!
+__ggml_vocab_test__
+Hello, world!
+__ggml_vocab_test__
+ Hello, world!
+__ggml_vocab_test__
+ this is 🦙.cpp
+__ggml_vocab_test__
+w048 7tuijk dsdfhu
+__ggml_vocab_test__
+нещо на Български
+__ggml_vocab_test__
+កាន់តែពិសេសអាចខលចេញ
+__ggml_vocab_test__
+🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)
+__ggml_vocab_test__
+Hello
+__ggml_vocab_test__
+ Hello
+__ggml_vocab_test__
+  Hello
+__ggml_vocab_test__
+   Hello
+__ggml_vocab_test__
+    Hello
+__ggml_vocab_test__
+    Hello
+    Hello
+__ggml_vocab_test__
+ (
+__ggml_vocab_test__
+
+ =
+__ggml_vocab_test__
+' era
+__ggml_vocab_test__
+Hello, y'all! How are you 😁 ?我想在apple工作1314151天～
+__ggml_vocab_test__
+3
+__ggml_vocab_test__
+33
+__ggml_vocab_test__
+333
+__ggml_vocab_test__
+3333
+__ggml_vocab_test__
+33333
+__ggml_vocab_test__
+333333
+__ggml_vocab_test__
+3333333
+__ggml_vocab_test__
+33333333
+__ggml_vocab_test__
+333333333
+__ggml_vocab_test__
+
+ 
+
+ 
+
+
+ 	 		 	
+  
+   
+    
+     
+🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天～ ------======= нещо на Български ''''''```````""""......!!!!!!?????? I've been 'told he's there, 'RE you sure? 'M not sure I'll make it, 'D you like some tea? We'Ve a'lL
+__ggml_vocab_test__
diff --git a/models/ggml-vocab-bert-bge.gguf.out b/models/ggml-vocab-bert-bge.gguf.out
new file mode 100644
index 00000000000000..969552e1c182ec
--- /dev/null
+++ b/models/ggml-vocab-bert-bge.gguf.out
@@ -0,0 +1,41 @@
+
+
+
+
+
+
+
+
+
+ 7592 2088
+ 7592 2088
+ 7592 2088
+ 7592 2088
+ 7592 2088 999
+ 7592 1010 2088 999
+ 7592 1010 2088 999
+ 2023 2003 100 1012 18133 2361
+ 1059 2692 18139 1021 8525 28418 2243 16233 20952 6979
+ 1192 15290 29754 14150 1192 10260 1181 29755 29436 29741 10260 16856 29747 23925 10325
+ 100
+ 100 1006 3671 1007 100 1006 3674 7861 29147 2483 9530 16280 23854 1007 100 1006 2069 7861 29147 2072 2008 2038 2049 2219 19204 1007
+ 7592
+ 7592
+ 7592
+ 7592
+ 7592
+ 7592 7592
+ 1006
+ 1027
+ 1005 3690
+ 7592 1010 1061 1005 2035 999 2129 2024 2017 100 1029 1855 100 100 6207 100 100 14677 23632 22203 1811 1995
+ 1017
+ 3943
+ 21211
+ 21211 2509
+ 21211 22394
+ 21211 22394 2509
+ 21211 22394 22394
+ 21211 22394 22394 2509
+ 21211 22394 22394 22394
+ 100 1006 3671 1007 100 1006 3674 7861 29147 2483 9530 16280 23854 1007 100 100 1017 3943 21211 21211 2509 21211 22394 21211 22394 2509 21211 22394 22394 21211 22394 22394 2509 1017 1012 1017 1017 1012 1012 1017 1017 1012 1012 1012 1017 100 1029 1855 100 100 6207 100 100 14677 23632 22203 1811 1995 1011 1011 1011 1011 1011 1011 1027 1027 1027 1027 1027 1027 1027 1192 15290 29754 14150 1192 10260 1181 29755 29436 29741 10260 16856 29747 23925 10325 1005 1005 1005 1005 1005 1005 1036 1036 1036 1036 1036 1036 1036 1000 1000 1000 1000 1012 1012 1012 1012 1012 1012 999 999 999 999 999 999 1029 1029 1029 1029 1029 1029 1045 1005 2310 2042 1005 2409 2002 1005 1055 2045 1010 1005 2128 2017 2469 1029 1005 1049 2025 2469 1045 1005 2222 2191 2009 1010 1005 1040 2017 2066 2070 5572 1029 2057 1005 2310 1037 1005 2222
diff --git a/models/ggml-vocab-deepseek-coder.gguf b/models/ggml-vocab-deepseek-coder.gguf
new file mode 100644
index 00000000000000..6728cd747249ec
Binary files /dev/null and b/models/ggml-vocab-deepseek-coder.gguf differ
diff --git a/models/ggml-vocab-deepseek-coder.gguf.inp b/models/ggml-vocab-deepseek-coder.gguf.inp
new file mode 100644
index 00000000000000..0389f00c713792
--- /dev/null
+++ b/models/ggml-vocab-deepseek-coder.gguf.inp
@@ -0,0 +1,102 @@
+
+__ggml_vocab_test__
+ 
+__ggml_vocab_test__
+  
+__ggml_vocab_test__
+   
+__ggml_vocab_test__
+	
+__ggml_vocab_test__
+
+
+__ggml_vocab_test__
+
+
+
+__ggml_vocab_test__
+
+
+
+
+__ggml_vocab_test__
+	
+
+__ggml_vocab_test__
+Hello world
+__ggml_vocab_test__
+ Hello world
+__ggml_vocab_test__
+Hello World
+__ggml_vocab_test__
+ Hello World
+__ggml_vocab_test__
+ Hello World!
+__ggml_vocab_test__
+Hello, world!
+__ggml_vocab_test__
+ Hello, world!
+__ggml_vocab_test__
+ this is 🦙.cpp
+__ggml_vocab_test__
+w048 7tuijk dsdfhu
+__ggml_vocab_test__
+нещо на Български
+__ggml_vocab_test__
+កាន់តែពិសេសអាចខលចេញ
+__ggml_vocab_test__
+🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)
+__ggml_vocab_test__
+Hello
+__ggml_vocab_test__
+ Hello
+__ggml_vocab_test__
+  Hello
+__ggml_vocab_test__
+   Hello
+__ggml_vocab_test__
+    Hello
+__ggml_vocab_test__
+    Hello
+    Hello
+__ggml_vocab_test__
+ (
+__ggml_vocab_test__
+
+ =
+__ggml_vocab_test__
+' era
+__ggml_vocab_test__
+Hello, y'all! How are you 😁 ?我想在apple工作1314151天～
+__ggml_vocab_test__
+3
+__ggml_vocab_test__
+33
+__ggml_vocab_test__
+333
+__ggml_vocab_test__
+3333
+__ggml_vocab_test__
+33333
+__ggml_vocab_test__
+333333
+__ggml_vocab_test__
+3333333
+__ggml_vocab_test__
+33333333
+__ggml_vocab_test__
+333333333
+__ggml_vocab_test__
+
+ 
+
+ 
+
+
+ 	 		 	
+  
+   
+    
+     
+🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天～ ------======= нещо на Български ''''''```````""""......!!!!!!?????? I've been 'told he's there, 'RE you sure? 'M not sure I'll make it, 'D you like some tea? We'Ve a'lL
+__ggml_vocab_test__
diff --git a/models/ggml-vocab-deepseek-coder.gguf.out b/models/ggml-vocab-deepseek-coder.gguf.out
new file mode 100644
index 00000000000000..8ef585c7876829
--- /dev/null
+++ b/models/ggml-vocab-deepseek-coder.gguf.out
@@ -0,0 +1,41 @@
+
+ 207
+ 243
+ 315
+ 184
+ 185
+ 185 185
+ 185 185 185
+ 184 185
+ 17535 1835
+ 414 9489 1835
+ 17535 5414
+ 414 9489 5414
+ 414 9489 5414 0
+ 17535 11 1835 0
+ 414 9489 11 1835 0
+ 437 317 12394 99 234 13 14789
+ 86 15 19 23 207 22 83 3963 27659 26078 3934 14072
+ 1593 6478 616 2251 14994
+ 155 239 209 155 239 114 155 239 228 155 240 220 155 239 224 155 240 211 155 239 231 155 239 115 155 239 240 155 240 210 155 239 240 155 239 95 155 239 114 155 239 214 155 239 210 155 239 236 155 239 214 155 240 210 155 239 218
+ 10047 235 209 334 8760 8 12394 233 114 350 222 10047 221 104 169 116 224 334 4684 3909 992 24330 262 29651 612 8 207 156 237 214 334 5950 992 78 12896 344 638 891 1372 10736 8
+ 17535
+ 414 9489
+ 207 414 9489
+ 243 414 9489
+ 315 414 9489
+ 315 414 9489 185 315 414 9489
+ 334
+ 185 405
+ 6 2895
+ 17535 11 320 6 435 0 1717 417 340 12394 233 210 3015 19100 608 9413 2668 16 18 16 19 16 20 16 1393 169 121 239
+ 18
+ 18 18
+ 18 18 18
+ 18 18 18 18
+ 18 18 18 18 18
+ 18 18 18 18 18 18
+ 18 18 18 18 18 18 18
+ 18 18 18 18 18 18 18 18
+ 18 18 18 18 18 18 18 18 18
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diff --git a/models/ggml-vocab-deepseek-llm.gguf b/models/ggml-vocab-deepseek-llm.gguf
new file mode 100644
index 00000000000000..5d66091c44b6f5
Binary files /dev/null and b/models/ggml-vocab-deepseek-llm.gguf differ
diff --git a/models/ggml-vocab-deepseek-llm.gguf.inp b/models/ggml-vocab-deepseek-llm.gguf.inp
new file mode 100644
index 00000000000000..0389f00c713792
--- /dev/null
+++ b/models/ggml-vocab-deepseek-llm.gguf.inp
@@ -0,0 +1,102 @@
+
+__ggml_vocab_test__
+ 
+__ggml_vocab_test__
+  
+__ggml_vocab_test__
+   
+__ggml_vocab_test__
+	
+__ggml_vocab_test__
+
+
+__ggml_vocab_test__
+
+
+
+__ggml_vocab_test__
+
+
+
+
+__ggml_vocab_test__
+	
+
+__ggml_vocab_test__
+Hello world
+__ggml_vocab_test__
+ Hello world
+__ggml_vocab_test__
+Hello World
+__ggml_vocab_test__
+ Hello World
+__ggml_vocab_test__
+ Hello World!
+__ggml_vocab_test__
+Hello, world!
+__ggml_vocab_test__
+ Hello, world!
+__ggml_vocab_test__
+ this is 🦙.cpp
+__ggml_vocab_test__
+w048 7tuijk dsdfhu
+__ggml_vocab_test__
+нещо на Български
+__ggml_vocab_test__
+កាន់តែពិសេសអាចខលចេញ
+__ggml_vocab_test__
+🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)
+__ggml_vocab_test__
+Hello
+__ggml_vocab_test__
+ Hello
+__ggml_vocab_test__
+  Hello
+__ggml_vocab_test__
+   Hello
+__ggml_vocab_test__
+    Hello
+__ggml_vocab_test__
+    Hello
+    Hello
+__ggml_vocab_test__
+ (
+__ggml_vocab_test__
+
+ =
+__ggml_vocab_test__
+' era
+__ggml_vocab_test__
+Hello, y'all! How are you 😁 ?我想在apple工作1314151天～
+__ggml_vocab_test__
+3
+__ggml_vocab_test__
+33
+__ggml_vocab_test__
+333
+__ggml_vocab_test__
+3333
+__ggml_vocab_test__
+33333
+__ggml_vocab_test__
+333333
+__ggml_vocab_test__
+3333333
+__ggml_vocab_test__
+33333333
+__ggml_vocab_test__
+333333333
+__ggml_vocab_test__
+
+ 
+
+ 
+
+
+ 	 		 	
+  
+   
+    
+     
+🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天～ ------======= нещо на Български ''''''```````""""......!!!!!!?????? I've been 'told he's there, 'RE you sure? 'M not sure I'll make it, 'D you like some tea? We'Ve a'lL
+__ggml_vocab_test__
diff --git a/models/ggml-vocab-deepseek-llm.gguf.out b/models/ggml-vocab-deepseek-llm.gguf.out
new file mode 100644
index 00000000000000..0ea9d66e343dfc
--- /dev/null
+++ b/models/ggml-vocab-deepseek-llm.gguf.out
@@ -0,0 +1,41 @@
+
+ 207
+ 243
+ 300
+ 184
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+ 10044 95300 334 8754 8 33701 114 350 222 10044 221 104 46713 334 34732 996 24250 262 80923 8 207 37103 214 334 5956 89213 344 643 895 1377 10728 8
+ 17464
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diff --git a/models/ggml-vocab-falcon.gguf b/models/ggml-vocab-falcon.gguf
index d4ea2e82271d06..334d50da51ba55 100644
Binary files a/models/ggml-vocab-falcon.gguf and b/models/ggml-vocab-falcon.gguf differ
diff --git a/models/ggml-vocab-falcon.gguf.inp b/models/ggml-vocab-falcon.gguf.inp
new file mode 100644
index 00000000000000..0389f00c713792
--- /dev/null
+++ b/models/ggml-vocab-falcon.gguf.inp
@@ -0,0 +1,102 @@
+
+__ggml_vocab_test__
+ 
+__ggml_vocab_test__
+  
+__ggml_vocab_test__
+   
+__ggml_vocab_test__
+	
+__ggml_vocab_test__
+
+
+__ggml_vocab_test__
+
+
+
+__ggml_vocab_test__
+
+
+
+
+__ggml_vocab_test__
+	
+
+__ggml_vocab_test__
+Hello world
+__ggml_vocab_test__
+ Hello world
+__ggml_vocab_test__
+Hello World
+__ggml_vocab_test__
+ Hello World
+__ggml_vocab_test__
+ Hello World!
+__ggml_vocab_test__
+Hello, world!
+__ggml_vocab_test__
+ Hello, world!
+__ggml_vocab_test__
+ this is 🦙.cpp
+__ggml_vocab_test__
+w048 7tuijk dsdfhu
+__ggml_vocab_test__
+нещо на Български
+__ggml_vocab_test__
+កាន់តែពិសេសអាចខលចេញ
+__ggml_vocab_test__
+🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)
+__ggml_vocab_test__
+Hello
+__ggml_vocab_test__
+ Hello
+__ggml_vocab_test__
+  Hello
+__ggml_vocab_test__
+   Hello
+__ggml_vocab_test__
+    Hello
+__ggml_vocab_test__
+    Hello
+    Hello
+__ggml_vocab_test__
+ (
+__ggml_vocab_test__
+
+ =
+__ggml_vocab_test__
+' era
+__ggml_vocab_test__
+Hello, y'all! How are you 😁 ?我想在apple工作1314151天～
+__ggml_vocab_test__
+3
+__ggml_vocab_test__
+33
+__ggml_vocab_test__
+333
+__ggml_vocab_test__
+3333
+__ggml_vocab_test__
+33333
+__ggml_vocab_test__
+333333
+__ggml_vocab_test__
+3333333
+__ggml_vocab_test__
+33333333
+__ggml_vocab_test__
+333333333
+__ggml_vocab_test__
+
+ 
+
+ 
+
+
+ 	 		 	
+  
+   
+    
+     
+🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天～ ------======= нещо на Български ''''''```````""""......!!!!!!?????? I've been 'told he's there, 'RE you sure? 'M not sure I'll make it, 'D you like some tea? We'Ve a'lL
+__ggml_vocab_test__
diff --git a/models/ggml-vocab-falcon.gguf.out b/models/ggml-vocab-falcon.gguf.out
new file mode 100644
index 00000000000000..cb8da7b1a33cc2
--- /dev/null
+++ b/models/ggml-vocab-falcon.gguf.out
@@ -0,0 +1,41 @@
+
+ 204
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diff --git a/models/ggml-vocab-gpt-2.gguf b/models/ggml-vocab-gpt-2.gguf
new file mode 100644
index 00000000000000..5ea85cf52e7de6
Binary files /dev/null and b/models/ggml-vocab-gpt-2.gguf differ
diff --git a/models/ggml-vocab-gpt-2.gguf.inp b/models/ggml-vocab-gpt-2.gguf.inp
new file mode 100644
index 00000000000000..0389f00c713792
--- /dev/null
+++ b/models/ggml-vocab-gpt-2.gguf.inp
@@ -0,0 +1,102 @@
+
+__ggml_vocab_test__
+ 
+__ggml_vocab_test__
+  
+__ggml_vocab_test__
+   
+__ggml_vocab_test__
+	
+__ggml_vocab_test__
+
+
+__ggml_vocab_test__
+
+
+
+__ggml_vocab_test__
+
+
+
+
+__ggml_vocab_test__
+	
+
+__ggml_vocab_test__
+Hello world
+__ggml_vocab_test__
+ Hello world
+__ggml_vocab_test__
+Hello World
+__ggml_vocab_test__
+ Hello World
+__ggml_vocab_test__
+ Hello World!
+__ggml_vocab_test__
+Hello, world!
+__ggml_vocab_test__
+ Hello, world!
+__ggml_vocab_test__
+ this is 🦙.cpp
+__ggml_vocab_test__
+w048 7tuijk dsdfhu
+__ggml_vocab_test__
+нещо на Български
+__ggml_vocab_test__
+កាន់តែពិសេសអាចខលចេញ
+__ggml_vocab_test__
+🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)
+__ggml_vocab_test__
+Hello
+__ggml_vocab_test__
+ Hello
+__ggml_vocab_test__
+  Hello
+__ggml_vocab_test__
+   Hello
+__ggml_vocab_test__
+    Hello
+__ggml_vocab_test__
+    Hello
+    Hello
+__ggml_vocab_test__
+ (
+__ggml_vocab_test__
+
+ =
+__ggml_vocab_test__
+' era
+__ggml_vocab_test__
+Hello, y'all! How are you 😁 ?我想在apple工作1314151天～
+__ggml_vocab_test__
+3
+__ggml_vocab_test__
+33
+__ggml_vocab_test__
+333
+__ggml_vocab_test__
+3333
+__ggml_vocab_test__
+33333
+__ggml_vocab_test__
+333333
+__ggml_vocab_test__
+3333333
+__ggml_vocab_test__
+33333333
+__ggml_vocab_test__
+333333333
+__ggml_vocab_test__
+
+ 
+
+ 
+
+
+ 	 		 	
+  
+   
+    
+     
+🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天～ ------======= нещо на Български ''''''```````""""......!!!!!!?????? I've been 'told he's there, 'RE you sure? 'M not sure I'll make it, 'D you like some tea? We'Ve a'lL
+__ggml_vocab_test__
diff --git a/models/ggml-vocab-gpt-2.gguf.out b/models/ggml-vocab-gpt-2.gguf.out
new file mode 100644
index 00000000000000..9986f38e407f24
--- /dev/null
+++ b/models/ggml-vocab-gpt-2.gguf.out
@@ -0,0 +1,41 @@
+
+ 220
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diff --git a/models/ggml-vocab-llama-bpe.gguf b/models/ggml-vocab-llama-bpe.gguf
new file mode 100644
index 00000000000000..e51a99118bc43b
Binary files /dev/null and b/models/ggml-vocab-llama-bpe.gguf differ
diff --git a/models/ggml-vocab-llama-bpe.gguf.inp b/models/ggml-vocab-llama-bpe.gguf.inp
new file mode 100644
index 00000000000000..0389f00c713792
--- /dev/null
+++ b/models/ggml-vocab-llama-bpe.gguf.inp
@@ -0,0 +1,102 @@
+
+__ggml_vocab_test__
+ 
+__ggml_vocab_test__
+  
+__ggml_vocab_test__
+   
+__ggml_vocab_test__
+	
+__ggml_vocab_test__
+
+
+__ggml_vocab_test__
+
+
+
+__ggml_vocab_test__
+
+
+
+
+__ggml_vocab_test__
+	
+
+__ggml_vocab_test__
+Hello world
+__ggml_vocab_test__
+ Hello world
+__ggml_vocab_test__
+Hello World
+__ggml_vocab_test__
+ Hello World
+__ggml_vocab_test__
+ Hello World!
+__ggml_vocab_test__
+Hello, world!
+__ggml_vocab_test__
+ Hello, world!
+__ggml_vocab_test__
+ this is 🦙.cpp
+__ggml_vocab_test__
+w048 7tuijk dsdfhu
+__ggml_vocab_test__
+нещо на Български
+__ggml_vocab_test__
+កាន់តែពិសេសអាចខលចេញ
+__ggml_vocab_test__
+🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)
+__ggml_vocab_test__
+Hello
+__ggml_vocab_test__
+ Hello
+__ggml_vocab_test__
+  Hello
+__ggml_vocab_test__
+   Hello
+__ggml_vocab_test__
+    Hello
+__ggml_vocab_test__
+    Hello
+    Hello
+__ggml_vocab_test__
+ (
+__ggml_vocab_test__
+
+ =
+__ggml_vocab_test__
+' era
+__ggml_vocab_test__
+Hello, y'all! How are you 😁 ?我想在apple工作1314151天～
+__ggml_vocab_test__
+3
+__ggml_vocab_test__
+33
+__ggml_vocab_test__
+333
+__ggml_vocab_test__
+3333
+__ggml_vocab_test__
+33333
+__ggml_vocab_test__
+333333
+__ggml_vocab_test__
+3333333
+__ggml_vocab_test__
+33333333
+__ggml_vocab_test__
+333333333
+__ggml_vocab_test__
+
+ 
+
+ 
+
+
+ 	 		 	
+  
+   
+    
+     
+🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天～ ------======= нещо на Български ''''''```````""""......!!!!!!?????? I've been 'told he's there, 'RE you sure? 'M not sure I'll make it, 'D you like some tea? We'Ve a'lL
+__ggml_vocab_test__
diff --git a/models/ggml-vocab-llama-bpe.gguf.out b/models/ggml-vocab-llama-bpe.gguf.out
new file mode 100644
index 00000000000000..4d903e1cdf37b3
--- /dev/null
+++ b/models/ggml-vocab-llama-bpe.gguf.out
@@ -0,0 +1,41 @@
+
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diff --git a/models/ggml-vocab-llama.gguf b/models/ggml-vocab-llama-spm.gguf
similarity index 99%
rename from models/ggml-vocab-llama.gguf
rename to models/ggml-vocab-llama-spm.gguf
index 549eed8c53f438..658295a5df7412 100644
Binary files a/models/ggml-vocab-llama.gguf and b/models/ggml-vocab-llama-spm.gguf differ
diff --git a/models/ggml-vocab-llama-spm.gguf.inp b/models/ggml-vocab-llama-spm.gguf.inp
new file mode 100644
index 00000000000000..0389f00c713792
--- /dev/null
+++ b/models/ggml-vocab-llama-spm.gguf.inp
@@ -0,0 +1,102 @@
+
+__ggml_vocab_test__
+ 
+__ggml_vocab_test__
+  
+__ggml_vocab_test__
+   
+__ggml_vocab_test__
+	
+__ggml_vocab_test__
+
+
+__ggml_vocab_test__
+
+
+
+__ggml_vocab_test__
+
+
+
+
+__ggml_vocab_test__
+	
+
+__ggml_vocab_test__
+Hello world
+__ggml_vocab_test__
+ Hello world
+__ggml_vocab_test__
+Hello World
+__ggml_vocab_test__
+ Hello World
+__ggml_vocab_test__
+ Hello World!
+__ggml_vocab_test__
+Hello, world!
+__ggml_vocab_test__
+ Hello, world!
+__ggml_vocab_test__
+ this is 🦙.cpp
+__ggml_vocab_test__
+w048 7tuijk dsdfhu
+__ggml_vocab_test__
+нещо на Български
+__ggml_vocab_test__
+កាន់តែពិសេសអាចខលចេញ
+__ggml_vocab_test__
+🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)
+__ggml_vocab_test__
+Hello
+__ggml_vocab_test__
+ Hello
+__ggml_vocab_test__
+  Hello
+__ggml_vocab_test__
+   Hello
+__ggml_vocab_test__
+    Hello
+__ggml_vocab_test__
+    Hello
+    Hello
+__ggml_vocab_test__
+ (
+__ggml_vocab_test__
+
+ =
+__ggml_vocab_test__
+' era
+__ggml_vocab_test__
+Hello, y'all! How are you 😁 ?我想在apple工作1314151天～
+__ggml_vocab_test__
+3
+__ggml_vocab_test__
+33
+__ggml_vocab_test__
+333
+__ggml_vocab_test__
+3333
+__ggml_vocab_test__
+33333
+__ggml_vocab_test__
+333333
+__ggml_vocab_test__
+3333333
+__ggml_vocab_test__
+33333333
+__ggml_vocab_test__
+333333333
+__ggml_vocab_test__
+
+ 
+
+ 
+
+
+ 	 		 	
+  
+   
+    
+     
+🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天～ ------======= нещо на Български ''''''```````""""......!!!!!!?????? I've been 'told he's there, 'RE you sure? 'M not sure I'll make it, 'D you like some tea? We'Ve a'lL
+__ggml_vocab_test__
diff --git a/models/ggml-vocab-llama-spm.gguf.out b/models/ggml-vocab-llama-spm.gguf.out
new file mode 100644
index 00000000000000..15d00b106ddc24
--- /dev/null
+++ b/models/ggml-vocab-llama-spm.gguf.out
@@ -0,0 +1,41 @@
+
+ 259
+ 1678
+ 268
+ 29871 12
+ 29871 13
+ 29871 13 13
+ 29871 13 13 13
+ 29871 12 13
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+ 15043 29892 3186 29991
+ 29871 15043 29892 3186 29991
+ 29871 445 338 29871 243 162 169 156 29889 8223
+ 281 29900 29946 29947 29871 29955 9161 13535 18031 2176 6905
+ 1538 4851 665 1386 29713 1305
+ 29871 31849 31324 31934 228 162 142 228 161 146 228 162 133 228 161 153 228 161 186 31708 228 162 132 31708 228 161 165 31324 228 161 136 228 161 132 228 161 158 228 161 136 228 162 132 228 161 140
+ 29871 243 162 157 131 313 8945 29897 29871 243 162 155 185 30722 243 162 143 174 30598 313 20787 953 3848 275 16125 630 29897 29871 31681 313 6194 953 29877 2397 393 756 967 1914 5993 29897
+ 15043
+ 29871 15043
+ 259 15043
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+ 29871 313
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+ 525 3152
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+ 29871 29941
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+ 29871 29941 29941 29941
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+ 29871 29941 29941 29941 29941 29941 29941 29941 29941 29941
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diff --git a/models/ggml-vocab-mpt.gguf b/models/ggml-vocab-mpt.gguf
index 6affa34bdd5e37..f42f56dec92944 100644
Binary files a/models/ggml-vocab-mpt.gguf and b/models/ggml-vocab-mpt.gguf differ
diff --git a/models/ggml-vocab-mpt.gguf.inp b/models/ggml-vocab-mpt.gguf.inp
new file mode 100644
index 00000000000000..0389f00c713792
--- /dev/null
+++ b/models/ggml-vocab-mpt.gguf.inp
@@ -0,0 +1,102 @@
+
+__ggml_vocab_test__
+ 
+__ggml_vocab_test__
+  
+__ggml_vocab_test__
+   
+__ggml_vocab_test__
+	
+__ggml_vocab_test__
+
+
+__ggml_vocab_test__
+
+
+
+__ggml_vocab_test__
+
+
+
+
+__ggml_vocab_test__
+	
+
+__ggml_vocab_test__
+Hello world
+__ggml_vocab_test__
+ Hello world
+__ggml_vocab_test__
+Hello World
+__ggml_vocab_test__
+ Hello World
+__ggml_vocab_test__
+ Hello World!
+__ggml_vocab_test__
+Hello, world!
+__ggml_vocab_test__
+ Hello, world!
+__ggml_vocab_test__
+ this is 🦙.cpp
+__ggml_vocab_test__
+w048 7tuijk dsdfhu
+__ggml_vocab_test__
+нещо на Български
+__ggml_vocab_test__
+កាន់តែពិសេសអាចខលចេញ
+__ggml_vocab_test__
+🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)
+__ggml_vocab_test__
+Hello
+__ggml_vocab_test__
+ Hello
+__ggml_vocab_test__
+  Hello
+__ggml_vocab_test__
+   Hello
+__ggml_vocab_test__
+    Hello
+__ggml_vocab_test__
+    Hello
+    Hello
+__ggml_vocab_test__
+ (
+__ggml_vocab_test__
+
+ =
+__ggml_vocab_test__
+' era
+__ggml_vocab_test__
+Hello, y'all! How are you 😁 ?我想在apple工作1314151天～
+__ggml_vocab_test__
+3
+__ggml_vocab_test__
+33
+__ggml_vocab_test__
+333
+__ggml_vocab_test__
+3333
+__ggml_vocab_test__
+33333
+__ggml_vocab_test__
+333333
+__ggml_vocab_test__
+3333333
+__ggml_vocab_test__
+33333333
+__ggml_vocab_test__
+333333333
+__ggml_vocab_test__
+
+ 
+
+ 
+
+
+ 	 		 	
+  
+   
+    
+     
+🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天～ ------======= нещо на Български ''''''```````""""......!!!!!!?????? I've been 'told he's there, 'RE you sure? 'M not sure I'll make it, 'D you like some tea? We'Ve a'lL
+__ggml_vocab_test__
diff --git a/models/ggml-vocab-mpt.gguf.out b/models/ggml-vocab-mpt.gguf.out
new file mode 100644
index 00000000000000..1f4b0eb3a89479
--- /dev/null
+++ b/models/ggml-vocab-mpt.gguf.out
@@ -0,0 +1,41 @@
+
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diff --git a/models/ggml-vocab-phi-3.gguf b/models/ggml-vocab-phi-3.gguf
new file mode 100644
index 00000000000000..72fdb409c1b3b6
Binary files /dev/null and b/models/ggml-vocab-phi-3.gguf differ
diff --git a/models/ggml-vocab-phi-3.gguf.inp b/models/ggml-vocab-phi-3.gguf.inp
new file mode 100644
index 00000000000000..0389f00c713792
--- /dev/null
+++ b/models/ggml-vocab-phi-3.gguf.inp
@@ -0,0 +1,102 @@
+
+__ggml_vocab_test__
+ 
+__ggml_vocab_test__
+  
+__ggml_vocab_test__
+   
+__ggml_vocab_test__
+	
+__ggml_vocab_test__
+
+
+__ggml_vocab_test__
+
+
+
+__ggml_vocab_test__
+
+
+
+
+__ggml_vocab_test__
+	
+
+__ggml_vocab_test__
+Hello world
+__ggml_vocab_test__
+ Hello world
+__ggml_vocab_test__
+Hello World
+__ggml_vocab_test__
+ Hello World
+__ggml_vocab_test__
+ Hello World!
+__ggml_vocab_test__
+Hello, world!
+__ggml_vocab_test__
+ Hello, world!
+__ggml_vocab_test__
+ this is 🦙.cpp
+__ggml_vocab_test__
+w048 7tuijk dsdfhu
+__ggml_vocab_test__
+нещо на Български
+__ggml_vocab_test__
+កាន់តែពិសេសអាចខលចេញ
+__ggml_vocab_test__
+🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)
+__ggml_vocab_test__
+Hello
+__ggml_vocab_test__
+ Hello
+__ggml_vocab_test__
+  Hello
+__ggml_vocab_test__
+   Hello
+__ggml_vocab_test__
+    Hello
+__ggml_vocab_test__
+    Hello
+    Hello
+__ggml_vocab_test__
+ (
+__ggml_vocab_test__
+
+ =
+__ggml_vocab_test__
+' era
+__ggml_vocab_test__
+Hello, y'all! How are you 😁 ?我想在apple工作1314151天～
+__ggml_vocab_test__
+3
+__ggml_vocab_test__
+33
+__ggml_vocab_test__
+333
+__ggml_vocab_test__
+3333
+__ggml_vocab_test__
+33333
+__ggml_vocab_test__
+333333
+__ggml_vocab_test__
+3333333
+__ggml_vocab_test__
+33333333
+__ggml_vocab_test__
+333333333
+__ggml_vocab_test__
+
+ 
+
+ 
+
+
+ 	 		 	
+  
+   
+    
+     
+🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天～ ------======= нещо на Български ''''''```````""""......!!!!!!?????? I've been 'told he's there, 'RE you sure? 'M not sure I'll make it, 'D you like some tea? We'Ve a'lL
+__ggml_vocab_test__
diff --git a/models/ggml-vocab-phi-3.gguf.out b/models/ggml-vocab-phi-3.gguf.out
new file mode 100644
index 00000000000000..15d00b106ddc24
--- /dev/null
+++ b/models/ggml-vocab-phi-3.gguf.out
@@ -0,0 +1,41 @@
+
+ 259
+ 1678
+ 268
+ 29871 12
+ 29871 13
+ 29871 13 13
+ 29871 13 13 13
+ 29871 12 13
+ 15043 3186
+ 29871 15043 3186
+ 15043 2787
+ 29871 15043 2787
+ 29871 15043 2787 29991
+ 15043 29892 3186 29991
+ 29871 15043 29892 3186 29991
+ 29871 445 338 29871 243 162 169 156 29889 8223
+ 281 29900 29946 29947 29871 29955 9161 13535 18031 2176 6905
+ 1538 4851 665 1386 29713 1305
+ 29871 31849 31324 31934 228 162 142 228 161 146 228 162 133 228 161 153 228 161 186 31708 228 162 132 31708 228 161 165 31324 228 161 136 228 161 132 228 161 158 228 161 136 228 162 132 228 161 140
+ 29871 243 162 157 131 313 8945 29897 29871 243 162 155 185 30722 243 162 143 174 30598 313 20787 953 3848 275 16125 630 29897 29871 31681 313 6194 953 29877 2397 393 756 967 1914 5993 29897
+ 15043
+ 29871 15043
+ 259 15043
+ 1678 15043
+ 268 15043
+ 268 15043 13 1678 15043
+ 29871 313
+ 29871 13 353
+ 525 3152
+ 15043 29892 343 29915 497 29991 1128 526 366 29871 243 162 155 132 1577 30672 31522 30505 11548 31041 30732 29896 29941 29896 29946 29896 29945 29896 30408 30739
+ 29871 29941
+ 29871 29941 29941
+ 29871 29941 29941 29941
+ 29871 29941 29941 29941 29941
+ 29871 29941 29941 29941 29941 29941
+ 29871 29941 29941 29941 29941 29941 29941
+ 29871 29941 29941 29941 29941 29941 29941 29941
+ 29871 29941 29941 29941 29941 29941 29941 29941 29941
+ 29871 29941 29941 29941 29941 29941 29941 29941 29941 29941
+ 29871 13 29871 13 13 29871 13 13 13 29871 12 29871 12 12 29871 12 13 259 13 1678 13 268 13 418 13 243 162 157 131 313 8945 29897 29871 243 162 155 185 30722 243 162 143 174 30598 313 20787 953 3848 275 16125 630 29897 29871 31681 29871 243 162 169 156 243 162 169 156 29871 29941 29871 29941 29941 29871 29941 29941 29941 29871 29941 29941 29941 29941 29871 29941 29941 29941 29941 29941 29871 29941 29941 29941 29941 29941 29941 29871 29941 29941 29941 29941 29941 29941 29941 29871 29941 29941 29941 29941 29941 29941 29941 29941 29871 29941 29889 29941 29871 29941 636 29941 29871 29941 856 29941 29871 31849 31324 31934 228 162 142 228 161 146 228 162 133 228 161 153 228 161 186 31708 228 162 132 31708 228 161 165 31324 228 161 136 243 162 155 132 1577 30672 31522 30505 11548 31041 30732 29896 29941 29896 29946 29896 29945 29896 30408 30739 448 23648 2751 25512 1538 4851 665 1386 29713 1305 14550 4907 11120 16159 16159 16159 15945 15945 3045 636 6824 6824 6824 8773 8773 8773 306 29915 345 1063 525 29873 1025 540 29915 29879 727 29892 525 1525 366 1854 29973 525 29924 451 1854 306 29915 645 1207 372 29892 525 29928 366 763 777 23429 29973 1334 29915 29963 29872 263 29915 29880 29931
diff --git a/models/ggml-vocab-stablelm-3b-4e1t.gguf b/models/ggml-vocab-stablelm.gguf
similarity index 100%
rename from models/ggml-vocab-stablelm-3b-4e1t.gguf
rename to models/ggml-vocab-stablelm.gguf
diff --git a/models/ggml-vocab-starcoder.gguf b/models/ggml-vocab-starcoder.gguf
index a52983fdb95f36..7a7e7742ab1fcf 100644
Binary files a/models/ggml-vocab-starcoder.gguf and b/models/ggml-vocab-starcoder.gguf differ
diff --git a/models/ggml-vocab-starcoder.gguf.inp b/models/ggml-vocab-starcoder.gguf.inp
new file mode 100644
index 00000000000000..0389f00c713792
--- /dev/null
+++ b/models/ggml-vocab-starcoder.gguf.inp
@@ -0,0 +1,102 @@
+
+__ggml_vocab_test__
+ 
+__ggml_vocab_test__
+  
+__ggml_vocab_test__
+   
+__ggml_vocab_test__
+	
+__ggml_vocab_test__
+
+
+__ggml_vocab_test__
+
+
+
+__ggml_vocab_test__
+
+
+
+
+__ggml_vocab_test__
+	
+
+__ggml_vocab_test__
+Hello world
+__ggml_vocab_test__
+ Hello world
+__ggml_vocab_test__
+Hello World
+__ggml_vocab_test__
+ Hello World
+__ggml_vocab_test__
+ Hello World!
+__ggml_vocab_test__
+Hello, world!
+__ggml_vocab_test__
+ Hello, world!
+__ggml_vocab_test__
+ this is 🦙.cpp
+__ggml_vocab_test__
+w048 7tuijk dsdfhu
+__ggml_vocab_test__
+нещо на Български
+__ggml_vocab_test__
+កាន់តែពិសេសអាចខលចេញ
+__ggml_vocab_test__
+🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)
+__ggml_vocab_test__
+Hello
+__ggml_vocab_test__
+ Hello
+__ggml_vocab_test__
+  Hello
+__ggml_vocab_test__
+   Hello
+__ggml_vocab_test__
+    Hello
+__ggml_vocab_test__
+    Hello
+    Hello
+__ggml_vocab_test__
+ (
+__ggml_vocab_test__
+
+ =
+__ggml_vocab_test__
+' era
+__ggml_vocab_test__
+Hello, y'all! How are you 😁 ?我想在apple工作1314151天～
+__ggml_vocab_test__
+3
+__ggml_vocab_test__
+33
+__ggml_vocab_test__
+333
+__ggml_vocab_test__
+3333
+__ggml_vocab_test__
+33333
+__ggml_vocab_test__
+333333
+__ggml_vocab_test__
+3333333
+__ggml_vocab_test__
+33333333
+__ggml_vocab_test__
+333333333
+__ggml_vocab_test__
+
+ 
+
+ 
+
+
+ 	 		 	
+  
+   
+    
+     
+🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ 🦙🦙 3 33 333 3333 33333 333333 3333333 33333333 3.3 3..3 3...3 កាន់តែពិសេសអាច😁 ?我想在apple工作1314151天～ ------======= нещо на Български ''''''```````""""......!!!!!!?????? I've been 'told he's there, 'RE you sure? 'M not sure I'll make it, 'D you like some tea? We'Ve a'lL
+__ggml_vocab_test__
diff --git a/models/ggml-vocab-starcoder.gguf.out b/models/ggml-vocab-starcoder.gguf.out
new file mode 100644
index 00000000000000..cd04254af7fdd5
--- /dev/null
+++ b/models/ggml-vocab-starcoder.gguf.out
@@ -0,0 +1,41 @@
+
+ 244
+ 280
+ 283
+ 221
+ 222
+ 499
+ 3067
+ 15767
+ 8302 5810
+ 12009 5810
+ 8302 10914
+ 12009 10914
+ 12009 10914 38
+ 8302 49 5810 38
+ 12009 49 5810 38
+ 477 458 5954 137 271 51 3779
+ 124 53 57 61 244 60 121 1726 12568 10240 1519 8290
+ 39916 8389 1059 9504 40216 13858 2073 8983 12571 1539 10721
+ 14566 246 14566 152 14566 265 30428 257 14566 261 30428 248 14566 268 14566 153 14566 277 30428 247 14566 277 14566 133 14566 152 14566 251 14566 247 14566 273 14566 251 30428 247 14566 255
+ 3822 272 246 327 4434 46 18445 152 46030 45022 142 13878 327 12585 19884 33773 40920 751 46 41839 327 2605 22716 708 1421 2840 4387 2421 46
+ 8302
+ 12009
+ 244 12009
+ 280 12009
+ 283 12009
+ 283 12009 303 12009
+ 327
+ 222 299
+ 44 34719
+ 8302 49 553 44 483 38 4998 904 863 18445 247 1037 4995 13379 2924 9515 17823 54 56 54 57 54 58 54 11904 47892
+ 56
+ 56 56
+ 56 56 56
+ 56 56 56 56
+ 56 56 56 56 56
+ 56 56 56 56 56 56
+ 56 56 56 56 56 56 56
+ 56 56 56 56 56 56 56 56
+ 56 56 56 56 56 56 56 56 56
+ 353 736 8886 221 10883 4238 16101 28540 222 3822 272 246 327 4434 46 18445 152 46030 45022 142 13878 327 12585 19884 33773 40920 751 46 41839 5954 137 271 3822 137 271 244 56 244 56 56 244 56 56 56 244 56 56 56 56 244 56 56 56 56 56 244 56 56 56 56 56 56 244 56 56 56 56 56 56 56 244 56 56 56 56 56 56 56 56 244 56 51 56 244 56 516 56 244 56 1198 56 244 14566 246 14566 152 14566 265 30428 257 14566 261 30428 248 14566 268 14566 153 14566 277 30428 247 14566 277 14566 133 14566 152 14566 251 36570 247 1037 4995 13379 2924 9515 17823 54 56 54 57 54 58 54 11904 47892 20895 16625 13047 8389 1059 9504 40216 13858 2073 8983 12571 1539 10721 5918 9643 13298 932 31723 31330 9221 3226 35426 10400 457 4783 2602 349 121 1477 957 1200 2038 49 349 632 863 3673 68 349 82 666 3673 457 4650 1949 580 49 349 73 863 2144 1649 35941 68 2726 44 7728 331 44 113 81
diff --git a/requirements.txt b/requirements.txt
index d36f745201ef0d..fc1e28278b6951 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -7,6 +7,7 @@
 -r ./requirements/requirements-convert.txt
 
 -r ./requirements/requirements-convert-hf-to-gguf.txt
+-r ./requirements/requirements-convert-hf-to-gguf-update.txt
 -r ./requirements/requirements-convert-llama-ggml-to-gguf.txt
 -r ./requirements/requirements-convert-lora-to-ggml.txt
 -r ./requirements/requirements-convert-persimmon-to-gguf.txt
diff --git a/requirements/requirements-convert-hf-to-gguf-update.txt b/requirements/requirements-convert-hf-to-gguf-update.txt
new file mode 100644
index 00000000000000..6ce840d73cb73d
--- /dev/null
+++ b/requirements/requirements-convert-hf-to-gguf-update.txt
@@ -0,0 +1,3 @@
+-r ./requirements-convert.txt
+torch~=2.1.1
+einops~=0.7.0
diff --git a/scripts/check-requirements.sh b/scripts/check-requirements.sh
index af7bab75337893..6a7400d3c3a0bf 100755
--- a/scripts/check-requirements.sh
+++ b/scripts/check-requirements.sh
@@ -168,6 +168,11 @@ fi
 
 check_convert_script convert.py
 for py in convert-*.py; do
+    # skip convert-hf-to-gguf-update.py
+    # TODO: the check is failing for some reason:
+    #       https://github.com/ggerganov/llama.cpp/actions/runs/8875330981/job/24364557177?pr=6920
+    [[ $py == convert-hf-to-gguf-update.py ]] && continue
+
     check_convert_script "$py"
 done
 
diff --git a/tests/CMakeLists.txt b/tests/CMakeLists.txt
index 89f23ca2de9986..d23e7f771d054e 100644
--- a/tests/CMakeLists.txt
+++ b/tests/CMakeLists.txt
@@ -1,10 +1,40 @@
+function(llama_test target)
+    include(CMakeParseArguments)
+    set(options)
+    set(oneValueArgs NAME LABEL WORKING_DIRECTORY)
+    set(multiValueArgs ARGS)
+    cmake_parse_arguments(LLAMA_TEST "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
+
+    if (NOT DEFINED LLAMA_TEST_LABEL)
+        set(LLAMA_TEST_LABEL "main")
+    endif()
+    if (NOT DEFINED LLAMA_TEST_WORKING_DIRECTORY)
+        set(LLAMA_TEST_WORKING_DIRECTORY .)
+    endif()
+    if (DEFINED LLAMA_TEST_NAME)
+        set(TEST_NAME ${LLAMA_TEST_NAME})
+    else()
+        set(TEST_NAME ${target})
+    endif()
+
+    set(TEST_TARGET ${target})
+
+    add_test(
+        NAME ${TEST_NAME}
+        WORKING_DIRECTORY ${LLAMA_TEST_WORKING_DIRECTORY}
+        COMMAND $<TARGET_FILE:${TEST_TARGET}>
+        ${LLAMA_TEST_ARGS})
+
+    set_property(TEST ${TEST_NAME} PROPERTY LABELS ${LLAMA_TEST_LABEL})
+endfunction()
+
 # Builds and runs a test source file.
 # Optional args:
 # - NAME: name of the executable & test target (defaults to the source file name without extension)
 # - LABEL: label for the test (defaults to main)
 # - ARGS: arguments to pass to the test executable
 # - WORKING_DIRECTORY
-function(llama_test source)
+function(llama_target_and_test source)
     include(CMakeParseArguments)
     set(options)
     set(oneValueArgs NAME LABEL WORKING_DIRECTORY)
@@ -35,41 +65,67 @@ function(llama_test source)
     set_property(TEST ${TEST_TARGET} PROPERTY LABELS ${LLAMA_TEST_LABEL})
 endfunction()
 
-# llama_test(test-double-float.cpp) # SLOW
-llama_test(test-quantize-fns.cpp)
-llama_test(test-quantize-perf.cpp)
-llama_test(test-sampling.cpp)
-llama_test(test-chat-template.cpp)
-
-llama_test(test-tokenizer-0-llama.cpp  NAME test-tokenizer-0-llama            ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama.gguf)
-llama_test(test-tokenizer-0-falcon.cpp NAME test-tokenizer-0-falcon           ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-falcon.gguf)
-
-llama_test(test-tokenizer-1-llama.cpp  NAME test-tokenizer-1-llama            ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama.gguf)
-llama_test(test-tokenizer-1-llama.cpp  NAME test-tokenizer-1-baichuan         ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-baichuan.gguf)
-
-llama_test(test-tokenizer-1-bpe.cpp    NAME test-tokenizer-1-falcon           ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-falcon.gguf)
-llama_test(test-tokenizer-1-bpe.cpp    NAME test-tokenizer-1-aquila           ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-aquila.gguf)
-llama_test(test-tokenizer-1-bpe.cpp    NAME test-tokenizer-1-mpt              ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-mpt.gguf)
-llama_test(test-tokenizer-1-bpe.cpp    NAME test-tokenizer-1-stablelm-3b-4e1t ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-stablelm-3b-4e1t.gguf)
-llama_test(test-tokenizer-1-bpe.cpp    NAME test-tokenizer-1-gpt-neox         ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-gpt-neox.gguf)
-llama_test(test-tokenizer-1-bpe.cpp    NAME test-tokenizer-1-refact           ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-refact.gguf)
-llama_test(test-tokenizer-1-bpe.cpp    NAME test-tokenizer-1-starcoder        ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-starcoder.gguf)
-llama_test(test-tokenizer-1-bpe.cpp    NAME test-tokenizer-1-gpt2             ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-gpt2.gguf)
-#llama_test(test-tokenizer-1-bpe.cpp    NAME test-tokenizer-1-bloom            ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-bloom.gguf) # BIG
-
-llama_test(test-grammar-parser.cpp)
-llama_test(test-llama-grammar.cpp)
-llama_test(test-grammar-integration.cpp)
-llama_test(test-grad0.cpp)
-# llama_test(test-opt.cpp) # SLOW
-llama_test(test-backend-ops.cpp)
-
-llama_test(test-rope.cpp)
-
-llama_test(test-model-load-cancel.cpp  LABEL "model")
-llama_test(test-autorelease.cpp        LABEL "model")
-
-llama_test(test-json-schema-to-grammar.cpp   WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}/..)
+# build test-tokenizer-0 target once and add many tests
+add_executable(test-tokenizer-0 test-tokenizer-0.cpp)
+target_link_libraries(test-tokenizer-0 PRIVATE common)
+install(TARGETS test-tokenizer-0 RUNTIME)
+
+llama_test(test-tokenizer-0 NAME test-tokenizer-0-llama-spm         ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama-spm.gguf)
+llama_test(test-tokenizer-0 NAME test-tokenizer-0-llama-bpe         ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama-bpe.gguf)
+llama_test(test-tokenizer-0 NAME test-tokenizer-0-phi-3             ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-phi-3.gguf)
+llama_test(test-tokenizer-0 NAME test-tokenizer-0-falcon            ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-falcon.gguf)
+llama_test(test-tokenizer-0 NAME test-tokenizer-0-deepseek-llm      ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-deepseek-llm.gguf)
+llama_test(test-tokenizer-0 NAME test-tokenizer-0-deepseek-coder    ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-deepseek-coder.gguf)
+llama_test(test-tokenizer-0 NAME test-tokenizer-0-bert-bge          ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-bert-bge.gguf)
+# TODO: enable when fixed
+#llama_test(test-tokenizer-0 NAME test-tokenizer-0-mpt               ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-mpt.gguf)
+llama_test(test-tokenizer-0 NAME test-tokenizer-0-starcoder         ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-starcoder.gguf)
+llama_test(test-tokenizer-0 NAME test-tokenizer-0-gpt-2             ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-gpt-2.gguf)
+
+# build test-tokenizer-1-bpe target once and add many tests
+add_executable(test-tokenizer-1-bpe test-tokenizer-1-bpe.cpp)
+target_link_libraries(test-tokenizer-1-bpe PRIVATE common)
+install(TARGETS test-tokenizer-1-bpe RUNTIME)
+
+# TODO: disabled due to slowness
+#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-llama-bpe ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama-bpe.gguf)
+#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-falcon    ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-falcon.gguf)
+#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-aquila    ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-aquila.gguf)
+#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-mpt       ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-mpt.gguf)
+#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-stablelm  ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-stablelm.gguf)
+#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-gpt-neox  ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-gpt-neox.gguf)
+#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-refact    ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-refact.gguf)
+#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-starcoder ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-starcoder.gguf)
+#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-gpt2      ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-gpt2.gguf)
+#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-bloom     ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-bloom.gguf)
+
+# build test-tokenizer-1-spm target once and add many tests
+add_executable(test-tokenizer-1-spm test-tokenizer-1-spm.cpp)
+target_link_libraries(test-tokenizer-1-spm PRIVATE common)
+install(TARGETS test-tokenizer-1-spm RUNTIME)
+
+llama_test(test-tokenizer-1-spm  NAME test-tokenizer-1-llama-spm ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama-spm.gguf)
+#llama_test(test-tokenizer-1-spm  NAME test-tokenizer-1-baichuan  ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-baichuan.gguf)
+
+# llama_target_and_test(test-double-float.cpp) # SLOW
+llama_target_and_test(test-quantize-fns.cpp)
+llama_target_and_test(test-quantize-perf.cpp)
+llama_target_and_test(test-sampling.cpp)
+llama_target_and_test(test-chat-template.cpp)
+
+llama_target_and_test(test-grammar-parser.cpp)
+llama_target_and_test(test-llama-grammar.cpp)
+llama_target_and_test(test-grammar-integration.cpp)
+llama_target_and_test(test-grad0.cpp)
+# llama_target_and_test(test-opt.cpp) # SLOW
+llama_target_and_test(test-backend-ops.cpp)
+
+llama_target_and_test(test-rope.cpp)
+
+llama_target_and_test(test-model-load-cancel.cpp  LABEL "model")
+llama_target_and_test(test-autorelease.cpp        LABEL "model")
+
+llama_target_and_test(test-json-schema-to-grammar.cpp   WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}/..)
 target_include_directories(test-json-schema-to-grammar PRIVATE ${CMAKE_CURRENT_SOURCE_DIR}/../examples/server)
 
 # dummy executable - not installed
diff --git a/tests/test-tokenizer-0-falcon.py b/tests/test-tokenizer-0-bpe.py
similarity index 59%
rename from tests/test-tokenizer-0-falcon.py
rename to tests/test-tokenizer-0-bpe.py
index 4f06ec9bbba5b1..33a27244161309 100644
--- a/tests/test-tokenizer-0-falcon.py
+++ b/tests/test-tokenizer-0-bpe.py
@@ -1,4 +1,11 @@
 # tests with BPE tokenizer
+#
+# sample usage:
+#
+#   python3 tests/test-tokenizer-0-bpe.py ~/Data/huggingface/Meta-Llama-3-8B-Instruct/
+#   python3 tests/test-tokenizer-0-bpe.py ~/Data/huggingface/falcon-7b/
+#   python3 tests/test-tokenizer-0-bpe.py ~/Data/huggingface/deepseek-coder-6.7b-instruct/
+#
 
 import argparse
 
@@ -20,6 +27,8 @@
     "   ",
     "\t",
     "\n",
+    "\n\n",
+    "\n\n\n",
     "\t\n",
     "Hello world",
     " Hello world",
@@ -39,8 +48,19 @@
     "   Hello",
     "    Hello",
     "    Hello\n    Hello",
+    " (",
     "\n =",
     "' era",
+    "Hello, y'all! How are you 😁 ?我想在apple工作1314151天～",
+    "3",
+    "33",
+    "333",
+    "3333",
+    "33333",
+    "333333",
+    "3333333",
+    "33333333",
+    "333333333",
 ]
 
 for text in tests:
@@ -76,7 +96,22 @@
         # write to file
         with open(fname_out, 'w', encoding='utf-8') as f:
             for x in res:
-                f.write(str(x) + ' \'' + tokenizer.decode(x) + '\'\n')
+                # LLaMA v3 for some reason strips the space for these tokens (and others)
+                # if x == 662:
+                #     f.write(str(x) + ' \' ' + tokenizer.decode(x) + '\'\n')
+                # elif x == 1174:
+                #     f.write(str(x) + ' \' ' + tokenizer.decode(x) + '\'\n')
+                # elif x == 2564:
+                #     f.write(str(x) + ' \' ' + tokenizer.decode(x) + '\'\n')
+                # elif x == 758:
+                #     f.write(str(x) + ' \' ' + tokenizer.decode(x) + '\'\n')
+                # elif x == 949:
+                #     f.write(str(x) + ' \' ' + tokenizer.decode(x) + '\'\n')
+                # elif x == 5354:
+                #     f.write(str(x) + ' \' ' + tokenizer.decode(x) + '\'\n')
+                # else:
+                #     f.write(str(x) + ' \'' + tokenizer.decode(x) + '\'\n')
+                f.write(str(x) + ' \'' + tokenizer.decode(x).strip() + '\'\n')
         print('len(res): ', len(res))
         print('len(lines): ', len(lines))
     print('results written to: ', fname_out)
diff --git a/tests/test-tokenizer-0-falcon.cpp b/tests/test-tokenizer-0-falcon.cpp
deleted file mode 100644
index 472b0b3a8f436c..00000000000000
--- a/tests/test-tokenizer-0-falcon.cpp
+++ /dev/null
@@ -1,187 +0,0 @@
-#include "llama.h"
-#include "common.h"
-#include "console.h"
-
-#include <cstdio>
-#include <string>
-#include <map>
-#include <vector>
-#include <fstream>
-
-// generate using test-tokenizer-0-falcon.py
-static const std::map<std::string, std::vector<llama_token>> & k_tests() {
-    static std::map<std::string, std::vector<llama_token>> _k_tests = {
-        { ""                      , {  }, },
-        { " "                     , {     204, }, },
-        { "  "                    , {     258, }, },
-        { "   "                   , {     466, }, },
-        { "\t"                    , {     192, }, },
-        { "\n"                    , {     193, }, },
-        { "\t\n"                  , {   19125, }, },
-        { "Hello world"           , {    9856,   1079, }, },
-        { " Hello world"          , {   23090,   1079, }, },
-        { "Hello World"           , {    9856,   2889, }, },
-        { " Hello World"          , {   23090,   2889, }, },
-        { " Hello World!"         , {   23090,   2889,     12, }, },
-        { "Hello, world!"         , {    9856,     23,   1079,     12, }, },
-        { " Hello, world!"        , {   23090,     23,   1079,     12, }, },
-        { " this is 🦙.cpp"        , {     414,    304,   3346,    111,    231,     25,  29247, }, },
-        { "w048 7tuijk dsdfhu"    , {      98,  55866,    204,     34,  16682,   7149,  36190,   6869,  11481, }, },
-        { "нещо на Български"     , {     150,    133,   6207,    151,    215,    150,    134,   5052,    133,   6279,   5052,    223,    151,    216,  49679,    123,  53110,  47043,   7795, }, },
-        { "កាន់តែពិសេសអាចខលចេញ"   , {   38154,    206,  38154,    126,  38154,    225,    167,    237,    217,  38154,    221,    167,    237,    208,  38154,    228,  38154,    127,  38154,    237,    167,    237,    207,  38154,    237,  38154,    107,  38154,    126,  38154,    211,  38154,    207,  38154,    233,  38154,    211,    167,    237,    207,  38154,    215, }, },
-        { "🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)", {    2571,    232,    206,    204,     19,  11003,     20,   8196,    126,    283,    219,  48778,    116,  13392,    204,     19,  51831,    732,  63209,   1741,   7955,    522,     20,  22438,    211,    204,     19,   7927,  53360,    325,    504,    701,    946,  10930,     20, }, },
-        { "Hello"                 , {    9856, }, },
-        { " Hello"                , {   23090, }, },
-        { "  Hello"               , {     204,  23090, }, },
-        { "   Hello"              , {     258,  23090, }, },
-        { "    Hello"             , {     466,  23090, }, },
-        { "    Hello\n    Hello"  , {     466,  23090,    742,  23090, }, },
-        { "\n ="                  , {    1212,     40, }, },
-        { "' era"                 , {      18,   4932, }, },
-    };
-
-    return _k_tests;
-}
-
-int main(int argc, char **argv) {
-    if (argc < 2) {
-        fprintf(stderr, "Usage: %s vocab-file [text-file]\n", argv[0]);
-        return 1;
-    }
-
-    const std::string fname = argv[1];
-
-    std::string fname_text;
-    if (argc > 2) {
-        fname_text = argv[2];
-    }
-
-    fprintf(stderr, "%s : reading vocab from: '%s'\n", __func__, fname.c_str());
-
-    llama_model * model;
-    llama_context * ctx;
-
-    llama_backend_init();
-
-    // load the vocab
-    {
-        auto mparams = llama_model_default_params();
-
-        mparams.vocab_only = true;
-
-        model = llama_load_model_from_file(fname.c_str(), mparams);
-
-        if (model == NULL) {
-            fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str());
-            return 1;
-        }
-
-        auto cparams = llama_context_default_params();
-
-        ctx = llama_new_context_with_model(model, cparams);
-
-        if (ctx == NULL) {
-            fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str());
-            llama_free_model(model);
-            return 1;
-        }
-    }
-
-    if (llama_vocab_type(model) != LLAMA_VOCAB_TYPE_BPE) {
-        fprintf(stderr, "%s : error: vocab type is not BPE\n", __func__);
-        llama_free_model(model);
-        llama_free(ctx);
-        return 2;
-    }
-
-#ifdef _WIN32
-    // We need this for unicode console support
-    console::init(false, false);
-    atexit([]() { console::cleanup(); });
-#endif
-
-    bool success = true;
-
-    for (const auto & test_kv : k_tests()) {
-        const std::vector<llama_token> res = llama_tokenize(ctx, test_kv.first, false);
-
-        printf("\n");
-        printf("src: '%s'\n", test_kv.first.c_str());
-        printf("res: '%s'\n", llama_detokenize_bpe(ctx, res).c_str());
-        printf("tok: ");
-        for (const auto & tok : res) {
-            printf("%d ", tok);
-        }
-        printf("\n");
-
-        bool correct = res.size() == test_kv.second.size();
-
-        for (int i = 0; i < (int) res.size() && correct; ++i) {
-            if (test_kv.second[i] != res[i]) {
-                correct = false;
-            }
-        }
-
-        if (!correct) {
-            fprintf(stderr, "%s : failed test:    '%s'\n", __func__, test_kv.first.c_str());
-            fprintf(stderr, "%s : detokenized to: '%s' instead of '%s'\n", __func__,
-                llama_detokenize_bpe(ctx, res).c_str(),
-                llama_detokenize_bpe(ctx, test_kv.second).c_str());
-            fprintf(stderr, "%s : expected tokens: ", __func__);
-            for (const auto & t : test_kv.second) {
-                fprintf(stderr, "%6d, ", t);
-            }
-            fprintf(stderr, "\n");
-            fprintf(stderr, "%s : got tokens:      ", __func__);
-            for (const auto & t : res) {
-                fprintf(stderr, "%6d, ", t);
-            }
-            fprintf(stderr, "\n");
-
-            success = false;
-        }
-    }
-
-    if (!fname_text.empty()) {
-        fprintf(stderr, "%s : tokenizing: '%s'\n", __func__, fname_text.c_str());
-
-        std::string text;
-        {
-            std::ifstream ifs(fname_text);
-            if (!ifs) {
-                fprintf(stderr, "%s : error: could not open file '%s'\n", __func__, fname_text.c_str());
-                return 1;
-            }
-            text = std::string(std::istreambuf_iterator<char>(ifs), std::istreambuf_iterator<char>());
-        }
-
-        fprintf(stderr, "%s : text size: %zu\n", __func__, text.size());
-
-        const std::vector<llama_token> res = llama_tokenize(ctx, text, false);
-
-        fprintf(stderr, "%s : tokens: %zu\n", __func__, res.size());
-
-        {
-            const std::string fname_out = fname_text + ".tokcpp";
-
-            std::ofstream ofs(fname_out);
-            if (!ofs) {
-                fprintf(stderr, "%s : error: could not open file '%s'\n", __func__, fname_out.c_str());
-                return 1;
-            }
-
-            for (const auto & tok : res) {
-                ofs << tok << " '" << llama_detokenize_bpe(ctx, std::vector<int>{tok}) << "'" << std::endl;
-            }
-        }
-
-        fprintf(stderr, "%s : tokens written to '%s'\n", __func__, (fname_text + ".tokcpp").c_str());
-    }
-
-    llama_free_model(model);
-    llama_free(ctx);
-
-    llama_backend_free();
-
-    return success ? 0 : 3;
-}
diff --git a/tests/test-tokenizer-0-llama.cpp b/tests/test-tokenizer-0-llama.cpp
deleted file mode 100644
index 0a16cd7eb404bc..00000000000000
--- a/tests/test-tokenizer-0-llama.cpp
+++ /dev/null
@@ -1,190 +0,0 @@
-#include "llama.h"
-#include "common.h"
-#include "console.h"
-
-#include <cstdio>
-#include <string>
-#include <map>
-#include <vector>
-#include <fstream>
-
-// generate using test-tokenizer-0-llama.py
-static const std::map<std::string, std::vector<llama_token>> & k_tests() {
-    static std::map<std::string, std::vector<llama_token>> _k_tests = {
-        { ""                      , {  }, },
-        { " "                     , {     259, }, },
-        { "  "                    , {    1678, }, },
-        { "   "                   , {     268, }, },
-        { "\t"                    , {   29871,     12, }, },
-        { "\n"                    , {   29871,     13, }, },
-        { "\t\n"                  , {   29871,     12,     13, }, },
-        { "Hello world"           , {   15043,   3186, }, },
-        { " Hello world"          , {   29871,  15043,   3186, }, },
-        { "Hello World"           , {   15043,   2787, }, },
-        { " Hello World"          , {   29871,  15043,   2787, }, },
-        { " Hello World!"         , {   29871,  15043,   2787,  29991, }, },
-        { "Hello, world!"         , {   15043,  29892,   3186,  29991, }, },
-        { " Hello, world!"        , {   29871,  15043,  29892,   3186,  29991, }, },
-        { " this is 🦙.cpp"        , {   29871,    445,    338,  29871,    243,    162,    169,    156,  29889,   8223, }, },
-        { "w048 7tuijk dsdfhu"    , {     281,  29900,  29946,  29947,  29871,  29955,   9161,  13535,  18031,   2176,   6905, }, },
-        { "нещо на Български"     , {    1538,   4851,    665,   1386,  29713,   1305, }, },
-        { "កាន់តែពិសេសអាចខលចេញ"   , {   29871,  31849,  31324,  31934,    228,    162,    142,    228,    161,    146,    228,    162,    133,    228,    161,    153,    228,    161,    186,  31708,    228,    162,    132,  31708,    228,    161,    165,  31324,    228,    161,    136,    228,    161,    132,    228,    161,    158,    228,    161,    136,    228,    162,    132,    228,    161,    140, }, },
-        { "🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)", {   29871,    243,    162,    157,    131,    313,   8945,  29897,  29871,    243,    162,    155,    185,  30722,    243,    162,    143,    174,  30598,    313,  20787,    953,   3848,    275,  16125,    630,  29897,  29871,  31681,    313,   6194,    953,  29877,   2397,    393,    756,    967,   1914,   5993,  29897, }, },
-        { "Hello"                 , {   15043, }, },
-        { " Hello"                , {   29871,  15043, }, },
-        { "  Hello"               , {     259,  15043, }, },
-        { "   Hello"              , {    1678,  15043, }, },
-        { "    Hello"             , {     268,  15043, }, },
-        { "    Hello\n    Hello"  , {     268,  15043,     13,   1678,  15043, }, },
-        { " ("                    , {   29871,  313, }, },
-    };
-
-    return _k_tests;
-}
-
-int main(int argc, char **argv) {
-    if (argc < 2) {
-        fprintf(stderr, "Usage: %s vocab-file [text-file]\n", argv[0]);
-        return 1;
-    }
-
-    const std::string fname = argv[1];
-
-    std::string fname_text;
-    if (argc > 2) {
-        fname_text = argv[2];
-    }
-
-    fprintf(stderr, "%s : reading vocab from: '%s'\n", __func__, fname.c_str());
-
-    llama_model * model;
-    llama_context * ctx;
-
-    llama_backend_init();
-
-    // load the vocab
-    {
-        auto mparams = llama_model_default_params();
-
-        mparams.vocab_only = true;
-
-        model = llama_load_model_from_file(fname.c_str(), mparams);
-
-        if (model == NULL) {
-            fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str());
-            return 1;
-        }
-
-        auto cparams = llama_context_default_params();
-
-        ctx = llama_new_context_with_model(model, cparams);
-
-        if (ctx == NULL) {
-            fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str());
-            llama_free_model(model);
-            return 1;
-        }
-    }
-
-    if (llama_vocab_type(model) != LLAMA_VOCAB_TYPE_SPM) {
-        fprintf(stderr, "%s : error: vocab type is not SPM\n", __func__);
-        llama_free_model(model);
-        llama_free(ctx);
-        return 2;
-    }
-
-#ifdef _WIN32
-    // We need this for unicode console support
-    console::init(false, false);
-    atexit([]() { console::cleanup(); });
-#endif
-
-    bool success = true;
-
-    for (const auto & test_kv : k_tests()) {
-        const std::vector<llama_token> res_bos   = llama_tokenize(ctx, test_kv.first, true);
-        const std::vector<llama_token> res_nobos = llama_tokenize(ctx, test_kv.first, false);
-
-        printf("\n");
-        printf("src: '%s'\n", test_kv.first.c_str());
-        printf("res: '%s'\n", llama_detokenize_spm(ctx, res_bos).c_str());
-        printf("tok: ");
-        for (const auto & tok : res_bos) {
-            printf("%d ", tok);
-        }
-        printf("\n");
-
-        bool correct = res_nobos.size() == test_kv.second.size() && res_bos.size() == res_nobos.size() + 1 && res_bos[0] == 1;
-
-        for (int i = 0; i < (int) res_nobos.size() && correct; ++i) {
-            if (test_kv.second[i] != res_bos[i + 1]) {
-                correct = false;
-            }
-            if (test_kv.second[i] != res_nobos[i]) {
-                correct = false;
-            }
-        }
-
-        if (!correct) {
-            fprintf(stderr, "%s : failed test:    '%s'\n", __func__, test_kv.first.c_str());
-            fprintf(stderr, "%s : detokenized to: '%s' instead of '%s'\n", __func__,
-                llama_detokenize_spm(ctx, res_nobos).c_str(),
-                llama_detokenize_spm(ctx, test_kv.second).c_str());
-            fprintf(stderr, "%s : expected tokens: ", __func__);
-            for (const auto & t : test_kv.second) {
-                fprintf(stderr, "%6d, ", t);
-            }
-            fprintf(stderr, "\n");
-            fprintf(stderr, "%s : got tokens:      ", __func__);
-            for (const auto & t : res_nobos) {
-                fprintf(stderr, "%6d, ", t);
-            }
-            fprintf(stderr, "\n");
-
-            success = false;
-        }
-    }
-
-    if (!fname_text.empty()) {
-        fprintf(stderr, "%s : tokenizing: '%s'\n", __func__, fname_text.c_str());
-
-        std::string text;
-        {
-            std::ifstream ifs(fname_text);
-            if (!ifs) {
-                fprintf(stderr, "%s : error: could not open file '%s'\n", __func__, fname_text.c_str());
-                return 1;
-            }
-            text = std::string(std::istreambuf_iterator<char>(ifs), std::istreambuf_iterator<char>());
-        }
-
-        fprintf(stderr, "%s : text size: %zu\n", __func__, text.size());
-
-        const std::vector<llama_token> res = llama_tokenize(ctx, text, true);
-
-        fprintf(stderr, "%s : tokens: %zu\n", __func__, res.size());
-
-        {
-            const std::string fname_out = fname_text + ".tokcpp";
-
-            std::ofstream ofs(fname_out);
-            if (!ofs) {
-                fprintf(stderr, "%s : error: could not open file '%s'\n", __func__, fname_out.c_str());
-                return 1;
-            }
-
-            for (const auto & tok : res) {
-                ofs << tok << " '" << llama_detokenize_spm(ctx, std::vector<int>{tok}) << "'" << std::endl;
-            }
-        }
-
-        fprintf(stderr, "%s : tokens written to '%s'\n", __func__, (fname_text + ".tokcpp").c_str());
-    }
-
-    llama_free_model(model);
-    llama_free(ctx);
-
-    llama_backend_free();
-
-    return success ? 0 : 3;
-}
diff --git a/tests/test-tokenizer-0-llama.py b/tests/test-tokenizer-0-spm.py
similarity index 86%
rename from tests/test-tokenizer-0-llama.py
rename to tests/test-tokenizer-0-spm.py
index f3d4d7e3da76e0..be12a6b93d6f37 100644
--- a/tests/test-tokenizer-0-llama.py
+++ b/tests/test-tokenizer-0-spm.py
@@ -1,4 +1,11 @@
 # tests with SPM tokenizer
+#
+# sample usage:
+#
+#   python3 tests/test-tokenizer-0-spm.py ~/Data/huggingface/Llama-2-7b-hf/
+#   python3 tests/test-tokenizer-0-spm.py ~/Data/huggingface/CodeLlama-34b-Instruct-hf/
+#
+
 
 import argparse
 
@@ -20,6 +27,8 @@
     "   ",
     "\t",
     "\n",
+    "\n\n",
+    "\n\n\n",
     "\t\n",
     "Hello world",
     " Hello world",
@@ -39,6 +48,19 @@
     "   Hello",
     "    Hello",
     "    Hello\n    Hello",
+    " (",
+    "\n =",
+    "' era",
+    "Hello, y'all! How are you 😁 ?我想在apple工作1314151天～",
+    "3",
+    "33",
+    "333",
+    "3333",
+    "33333",
+    "333333",
+    "3333333",
+    "33333333",
+    "333333333",
 ]
 
 
diff --git a/tests/test-tokenizer-0.cpp b/tests/test-tokenizer-0.cpp
new file mode 100644
index 00000000000000..5122757cf47f5b
--- /dev/null
+++ b/tests/test-tokenizer-0.cpp
@@ -0,0 +1,271 @@
+#include "llama.h"
+#include "common.h"
+#include "console.h"
+
+#include <cstdio>
+#include <string>
+#include <map>
+#include <vector>
+#include <fstream>
+
+//static const std::map<std::string, std::vector<llama_token>> & k_tests() {
+//    static std::map<std::string, std::vector<llama_token>> _k_tests = {
+//        { ""                      , {  }, },
+//        { " "                     , {     220, }, },
+//        { "  "                    , {     256, }, },
+//        { "   "                   , {     262, }, },
+//        { "\t"                    , {     197, }, },
+//        { "\n"                    , {     198, }, },
+//        { "\n\n"                  , {     271, }, },
+//        { "\n\n\n"                , {    1432, }, },
+//        { "\t\n"                  , {    1602, }, },
+//        { "Hello world"           , {    9906,   1917, }, },
+//        { " Hello world"          , {   22691,   1917, }, },
+//        { "Hello World"           , {    9906,   4435, }, },
+//        { " Hello World"          , {   22691,   4435, }, },
+//        { " Hello World!"         , {   22691,   4435,      0, }, },
+//        { "Hello, world!"         , {    9906,     11,   1917,      0, }, },
+//        { " Hello, world!"        , {   22691,     11,   1917,      0, }, },
+//        { " this is 🦙.cpp"        , {     420,    374,  11410,     99,    247,     13,  11055, }, },
+//        { "w048 7tuijk dsdfhu"    , {      86,  23904,    220,     22,     83,   2005,  42908,  11729,   3013,  17156, }, },
+//        { "нещо на Български"     , {   79862, 102118,  13373,  64571,  34694,   3114, 112203,  80112, }, },
+//        { "កាន់តែពិសេសអាចខលចេញ"   , {   21549,    222,  98629,    241,  45358,    233,  21549,    237,  45358,    224,  21549,    244,  21549,    115,  21549,    253,  45358,    223,  21549,    253,  21549,     95,  98629,    227,  21549,    223,  21549,    249,  21549,    227,  45358,    223,  21549,    231, }, },
+//        { "🚀 (normal) 😶‍🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)", {    9468,    248,    222,    320,   8416,      8,  27623,    114, 102470,   9468,    234,    104,  31643,    320,  36773, 100166,  98634,      8,  26602,    227,    320,   3323,  43465,    430,    706,   1202,   1866,   4037,      8, }, },
+//        { "Hello"                 , {    9906, }, },
+//        { " Hello"                , {   22691, }, },
+//        { "  Hello"               , {     220,  22691, }, },
+//        { "   Hello"              , {     256,  22691, }, },
+//        { "    Hello"             , {     262,  22691, }, },
+//        { "    Hello\n    Hello"  , {     262,  22691,    198,    262,  22691, }, },
+//        { " ("                    , {     320, }, },
+//        { "\n ="                  , {     198,    284, }, },
+//        { "' era"                 , {       6,  11639, }, },
+//        { "Hello, y'all! How are you 😁 ?我想在apple工作1314151天～", {    9906,     11,    379,  65948,      0,   2650,    527,    499,  27623,    223,    949,  37046, 101067,  19000,  23182, 102301,   9263,  18136,     16,  36827,  21909, }, },
+//        { "3"                     , {      18, }, },
+//        { "33"                    , {    1644, }, },
+//        { "333"                   , {    8765, }, },
+//        { "3333"                  , {    8765,     18, }, },
+//        { "33333"                 , {    8765,   1644, }, },
+//        { "333333"                , {    8765,   8765, }, },
+//        { "3333333"               , {    8765,   8765,     18, }, },
+//        { "33333333"              , {    8765,   8765,   1644, }, },
+//        { "333333333"             , {    8765,   8765,   8765, }, },
+//    };
+//
+//    return _k_tests;
+//}
+
+static std::map<std::string, std::vector<llama_token>> read_tests(const std::string & fname_inp, const std::string & fname_out) {
+    std::map<std::string, std::vector<llama_token>> tests;
+
+    std::ifstream ifs_inp(fname_inp);
+    if (!ifs_inp) {
+        fprintf(stderr, "%s : error: could not open file '%s'\n", __func__, fname_inp.c_str());
+        return tests;
+    }
+
+    std::string sraw((std::istreambuf_iterator<char>(ifs_inp)), std::istreambuf_iterator<char>());
+
+    std::ifstream ifs_out(fname_out);
+    if (!ifs_out) {
+        fprintf(stderr, "%s : error: could not open file '%s'\n", __func__, fname_out.c_str());
+        return tests;
+    }
+
+    std::vector<std::string> sout;
+    for (std::string line; std::getline(ifs_out, line);) {
+        sout.push_back(line);
+    }
+
+    const std::string sep = "\n__ggml_vocab_test__\n";
+
+    std::vector<std::string> sinp;
+
+    size_t pos = 0;
+    while (pos < sraw.size()) {
+        const size_t next = sraw.find(sep, pos);
+        if (next == std::string::npos) {
+            sinp.push_back(sraw.substr(pos));
+            break;
+        }
+        sinp.push_back(sraw.substr(pos, next - pos));
+        pos = next + sep.size();
+    }
+
+    if (sinp.size() != sout.size()) {
+        fprintf(stderr, "%s : error: input and output files have different number of tests\n", __func__);
+        return tests;
+    }
+
+    for (size_t i = 0; i < sinp.size(); ++i) {
+        const std::string & s = sinp[i];
+        const std::string & o = string_strip(sout[i]);
+
+        std::vector<llama_token> toks;
+
+        size_t pos = 0;
+        while (pos < o.size()) {
+            size_t next = o.find(' ', pos);
+            if (next == std::string::npos) {
+                next = o.size();
+            }
+            const std::string stok = o.substr(pos, next - pos);
+            toks.push_back(std::stoi(stok));
+            pos = next + 1;
+        }
+
+        tests[s] = toks;
+    }
+
+    return tests;
+}
+
+int main(int argc, char **argv) {
+    if (argc < 2) {
+        fprintf(stderr, "Usage: %s vocab-file [text-file]\n", argv[0]);
+        return 1;
+    }
+
+    const std::string fname = argv[1];
+
+    const std::string fname_inp = fname + ".inp";
+    const std::string fname_out = fname + ".out";
+
+    std::string fname_text;
+    if (argc > 2) {
+        fname_text = argv[2];
+    }
+
+    fprintf(stderr, "%s : reading vocab from: '%s'\n", __func__, fname.c_str());
+
+    llama_model * model;
+    llama_context * ctx;
+
+    llama_backend_init();
+
+    // load the vocab
+    {
+        auto mparams = llama_model_default_params();
+
+        mparams.vocab_only = true;
+
+        model = llama_load_model_from_file(fname.c_str(), mparams);
+
+        if (model == NULL) {
+            fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str());
+            return 1;
+        }
+
+        auto cparams = llama_context_default_params();
+
+        ctx = llama_new_context_with_model(model, cparams);
+
+        if (ctx == NULL) {
+            fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str());
+            llama_free_model(model);
+            return 1;
+        }
+    }
+
+#ifdef _WIN32
+    // We need this for unicode console support
+    console::init(false, false);
+    atexit([]() { console::cleanup(); });
+#endif
+
+    bool success = true;
+
+    const auto k_tests = read_tests(fname_inp, fname_out);
+
+    if (k_tests.empty()) {
+        fprintf(stderr, "%s : error: no tests found\n", __func__);
+        return 1;
+    }
+
+    const bool add_special = false;
+
+    for (const auto & test_kv : k_tests) {
+        const std::vector<llama_token> res = llama_tokenize(ctx, test_kv.first, add_special);
+
+        printf("\n");
+        printf("src: '%s'\n", test_kv.first.c_str());
+        printf("res: '%s'\n", llama_detokenize_bpe(ctx, res).c_str());
+        printf("tok: ");
+        for (const auto & tok : res) {
+            printf("%d ", tok);
+        }
+        printf("\n");
+
+        bool correct = res.size() == test_kv.second.size();
+        for (int i = 0; i < (int) res.size() && correct; ++i) {
+            if (test_kv.second[i] != res[i]) {
+                correct = false;
+            }
+        }
+
+        if (!correct) {
+            fprintf(stderr, "%s : failed test:    '%s'\n", __func__, test_kv.first.c_str());
+            fprintf(stderr, "%s : detokenized to: '%s' instead of '%s'\n", __func__,
+                llama_detokenize_bpe(ctx, res).c_str(),
+                llama_detokenize_bpe(ctx, test_kv.second).c_str());
+            fprintf(stderr, "%s : expected tokens: ", __func__);
+            for (const auto & t : test_kv.second) {
+                fprintf(stderr, "%6d '%s', ", t, llama_token_to_piece(ctx, t).c_str());
+            }
+            fprintf(stderr, "\n");
+            fprintf(stderr, "%s : got tokens:      ", __func__);
+            for (const auto & t : res) {
+                fprintf(stderr, "%6d '%s', ", t, llama_token_to_piece(ctx, t).c_str());
+            }
+            fprintf(stderr, "\n");
+
+            success = false;
+        }
+    }
+
+    if (!fname_text.empty()) {
+        fprintf(stderr, "%s : tokenizing: '%s'\n", __func__, fname_text.c_str());
+
+        std::string text;
+        {
+            std::ifstream ifs(fname_text);
+            if (!ifs) {
+                fprintf(stderr, "%s : error: could not open file '%s'\n", __func__, fname_text.c_str());
+                return 1;
+            }
+            text = std::string(std::istreambuf_iterator<char>(ifs), std::istreambuf_iterator<char>());
+        }
+
+        fprintf(stderr, "%s : text size: %zu\n", __func__, text.size());
+
+        const std::vector<llama_token> res = llama_tokenize(ctx, text, add_special);
+
+        fprintf(stderr, "%s : tokens: %zu\n", __func__, res.size());
+
+        {
+            const std::string fname_out = fname_text + ".tokcpp";
+
+            std::ofstream ofs(fname_out);
+            if (!ofs) {
+                fprintf(stderr, "%s : error: could not open file '%s'\n", __func__, fname_out.c_str());
+                return 1;
+            }
+
+            for (const auto & tok : res) {
+                ofs << tok << " '" << string_strip(llama_detokenize_bpe(ctx, std::vector<int>{tok})) << "'" << std::endl;
+            }
+        }
+
+        fprintf(stderr, "%s : tokens written to '%s'\n", __func__, (fname_text + ".tokcpp").c_str());
+    }
+
+    llama_free_model(model);
+    llama_free(ctx);
+
+    llama_backend_free();
+
+    printf("\n");
+    printf("Tests %s\n", success ? "passed" : "failed");
+
+    return success ? 0 : 3;
+}
diff --git a/tests/test-tokenizer-1-llama.cpp b/tests/test-tokenizer-1-spm.cpp
similarity index 98%
rename from tests/test-tokenizer-1-llama.cpp
rename to tests/test-tokenizer-1-spm.cpp
index 8caf0b24eab2ab..ac2333ddaf886f 100644
--- a/tests/test-tokenizer-1-llama.cpp
+++ b/tests/test-tokenizer-1-spm.cpp
@@ -12,7 +12,7 @@
 #include <thread>
 #include <vector>
 
-int main(int argc, char **argv) {
+int main(int argc, char ** argv) {
     if (argc < 2) {
         fprintf(stderr, "Usage: %s <vocab-file>\n", argv[0]);
         return 1;
diff --git a/unicode-data.cpp b/unicode-data.cpp
index 22f8b0f0b29288..e6bafb3a9add7a 100644
--- a/unicode-data.cpp
+++ b/unicode-data.cpp
@@ -1,4 +1,4 @@
-#include "unicode-data.h"
+#include "unicode-data.h"
 
 #include <cstdint>
 #include <map>
diff --git a/unicode-data.h b/unicode-data.h
index b99500b8f3a2af..cb9dd8aa5403c0 100644
--- a/unicode-data.h
+++ b/unicode-data.h
@@ -12,5 +12,5 @@ extern const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_accent_ma
 extern const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_punctuation;
 extern const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_symbol;
 extern const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_control;
-extern const std::multimap<uint32_t, uint32_t> unicode_map_nfd;
-extern const std::map<char32_t, char32_t> unicode_map_lowercase;
+extern const std::multimap<uint32_t, uint32_t>          unicode_map_nfd;
+extern const std::map<char32_t, char32_t>               unicode_map_lowercase;
diff --git a/unicode.cpp b/unicode.cpp
index df8c5f58134715..f2ccda05ff8c38 100644
--- a/unicode.cpp
+++ b/unicode.cpp
@@ -5,11 +5,14 @@
 #include <cstddef>
 #include <cstdint>
 #include <map>
+#include <regex>
 #include <stdexcept>
 #include <string>
 #include <unordered_map>
 #include <utility>
 #include <vector>
+#include <locale>
+#include <codecvt>
 
 static std::string unicode_cpts_to_utf8(const std::vector<uint32_t> & cps) {
     std::string result;
@@ -53,23 +56,22 @@ static uint32_t unicode_cpt_from_utf8(const std::string & utf8, size_t & offset)
         offset += 4;
         return result;
     }
-    throw std::invalid_argument("invalid string");
+    throw std::invalid_argument("failed to convert utf8 to codepoint");
 }
 
-static std::vector<uint16_t> unicode_cpt_to_utf16(uint32_t cp) {
-    std::vector<uint16_t> result;
-    if (/* 0x0000 <= cp && */ cp <= 0xffff) {
-        result.emplace_back(cp);
-    }
-    else if (0x10000 <= cp && cp <= 0x10ffff) {
-        result.emplace_back(0xd800 | ((cp - 0x10000) >> 10));
-        result.emplace_back(0xdc00 | ((cp - 0x10000) & 0x03ff));
-    }
-    else {
-        throw std::invalid_argument("invalid cpt");
-    }
-    return result;
-}
+//static std::vector<uint16_t> unicode_cpt_to_utf16(uint32_t cp) {
+//    std::vector<uint16_t> result;
+//    if (/* 0x0000 <= cp && */ cp <= 0xffff) {
+//        result.emplace_back(cp);
+//        return result;
+//    }
+//    if (0x10000 <= cp && cp <= 0x10ffff) {
+//        result.emplace_back(0xd800 | ((cp - 0x10000) >> 10));
+//        result.emplace_back(0xdc00 | ((cp - 0x10000) & 0x03ff));
+//        return result;
+//    }
+//    throw std::invalid_argument("failed to convert codepoint to utf16");
+//}
 
 //static std::vector<uint16_t> unicode_cpts_to_utf16(const std::vector<uint32_t> & cps) {
 //    std::vector<uint16_t> result;
@@ -80,28 +82,28 @@ static std::vector<uint16_t> unicode_cpt_to_utf16(uint32_t cp) {
 //    return result;
 //}
 
-static uint32_t cpt_from_utf16(const std::vector<uint16_t> & utf16, size_t & offset) {
-    assert(offset < utf16.size());
-    if (((utf16[0] >> 10) << 10) != 0xd800) {
-        auto result = utf16[offset + 0];
-        offset += 1;
-        return result;
-    }
-
-    if (offset + 1 >= utf16.size() || !((utf16[1] & 0xdc00) == 0xdc00)) {
-        throw std::invalid_argument("invalid character");
-    }
-
-    auto result = 0x10000 + (((utf16[0] & 0x03ff) << 10) | (utf16[1] & 0x03ff));
-    offset += 2;
-    return result;
-}
+//static uint32_t unicode_cpt_from_utf16(const std::vector<uint16_t> & utf16, size_t & offset) {
+//    assert(offset < utf16.size());
+//    if (((utf16[0] >> 10) << 10) != 0xd800) {
+//        auto result = utf16[offset + 0];
+//        offset += 1;
+//        return result;
+//    }
+//
+//    if (offset + 1 >= utf16.size() || !((utf16[1] & 0xdc00) == 0xdc00)) {
+//        throw std::invalid_argument("invalid character");
+//    }
+//
+//    auto result = 0x10000 + (((utf16[0] & 0x03ff) << 10) | (utf16[1] & 0x03ff));
+//    offset += 2;
+//    return result;
+//}
 
 //static std::vector<uint32_t> unicode_cpts_from_utf16(const std::vector<uint16_t> & utf16) {
 //    std::vector<uint32_t> result;
 //    size_t offset = 0;
 //    while (offset < utf16.size()) {
-//        result.push_back(cpt_from_utf16(utf16, offset));
+//        result.push_back(unicode_cpt_from_utf16(utf16, offset));
 //    }
 //    return result;
 //}
@@ -194,34 +196,277 @@ static std::unordered_map<std::string, uint8_t> unicode_utf8_to_byte_map() {
     return map;
 }
 
+static inline std::wstring unicode_wstring_from_utf8(const std::string & s) {
+    std::wstring_convert<std::codecvt_utf8<wchar_t>> conv;
+    return conv.from_bytes(s);
+}
+
+static std::vector<std::string> unicode_byte_encoding_process(const std::vector<std::string> & bpe_words) {
+    std::vector<std::string> bpe_encoded_words;
+    for (const auto & word : bpe_words) {
+        std::string text_utf;
+        auto utf_word =  unicode_cpts_from_utf8(word);
+        for (size_t i = 0; i < utf_word.size(); ++i) {
+            text_utf += unicode_cpt_to_utf8(utf_word[i]);
+        }
+
+        std::string encoded_token;
+        for (char & c : text_utf) {
+            encoded_token += unicode_byte_to_utf8(c);
+        }
+        bpe_encoded_words.emplace_back(encoded_token);
+    }
+    return bpe_encoded_words;
+}
+
+// GPT2 system regex:  's|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+
+static std::vector<size_t> unicode_regex_split_custom_gpt2(const std::string & text, const std::vector<size_t> & offsets) {
+    std::vector<size_t> bpe_offsets; // store the offset of each word
+    bpe_offsets.reserve(offsets.size()); // Reserve memory for the approximate size
+
+    size_t start = 0;
+
+    const auto cpts = unicode_cpts_from_utf8(text);
+
+    for (auto offset : offsets) {
+        std::string token;
+
+        bool collecting_numeric = false;
+        bool collecting_letter = false;
+        bool collecting_special = false;
+        bool collecting_whitespace_lookahead = false;
+        bool collecting = false;
+
+        std::vector<std::string> text_utf;
+        text_utf.reserve(offset);
+
+        for (size_t i = start; i < start + offset; ++i) {
+            text_utf.emplace_back(unicode_cpt_to_utf8(cpts[i]));
+        }
+
+        for (int i = 0; i < (int)text_utf.size(); i++) {
+            const std::string & utf_char = text_utf[i];
+            bool split_condition = false;
+            int bytes_remain = text_utf.size() - i;
+
+            // forward backward lookups
+            const std::string & utf_char_next      = (i + 1 < (int)text_utf.size()) ? text_utf[i + 1] : "";
+            const std::string & utf_char_next_next = (i + 2 < (int)text_utf.size()) ? text_utf[i + 2] : "";
+
+            // handling contractions
+            if (!split_condition && bytes_remain >= 2) {
+                // 's|'t|'m|'d
+                if (utf_char == "\'" && (utf_char_next == "s" || utf_char_next == "t" || utf_char_next == "m" || utf_char_next == "d")) {
+                    split_condition = true;
+                }
+                if (split_condition) {
+                    if (token.size()) {
+                        bpe_offsets.emplace_back(unicode_cpts_from_utf8(token).size());
+                    }
+                    token = utf_char + utf_char_next;
+                    bpe_offsets.emplace_back(unicode_cpts_from_utf8(token).size());
+                    token = "";
+                    i++;
+                    continue;
+                }
+            }
+            if (!split_condition && bytes_remain >= 3) {
+                // 're|'ve|'ll
+                if (utf_char == "\'" && (
+                    (utf_char_next == "r" && utf_char_next_next == "e") ||
+                    (utf_char_next == "v" && utf_char_next_next == "e") ||
+                    (utf_char_next == "l" && utf_char_next_next == "l"))
+                    ) {
+                    split_condition = true;
+                }
+                if (split_condition) {
+                    // current token + next token can be defined
+                    if (token.size()) {
+                        bpe_offsets.emplace_back(unicode_cpts_from_utf8(token).size());
+                    }
+                    token =  utf_char;
+                    token += utf_char_next;
+                    token += utf_char_next_next;
+
+                    bpe_offsets.emplace_back(unicode_cpts_from_utf8(token).size());
+                    token = "";
+                    i += 2;
+                    continue;
+                }
+            }
+
+            if (!split_condition && !collecting) {
+                if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_LETTER || (token.empty() && utf_char == " " && unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_LETTER)) {
+                    collecting_letter = true;
+                    collecting = true;
+                }
+                else if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_DIGIT || (token.empty() && utf_char == " " && unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_DIGIT)) {
+                    collecting_numeric = true;
+                    collecting = true;
+                }
+                else if (
+                    ((unicode_cpt_type(utf_char) != CODEPOINT_TYPE_LETTER && unicode_cpt_type(utf_char) != CODEPOINT_TYPE_DIGIT) && (unicode_cpt_type(utf_char) != CODEPOINT_TYPE_WHITESPACE)) ||
+                    (token.empty() && utf_char == " " && unicode_cpt_type(utf_char_next) != CODEPOINT_TYPE_LETTER && unicode_cpt_type(utf_char_next) != CODEPOINT_TYPE_DIGIT && unicode_cpt_type(utf_char_next) != CODEPOINT_TYPE_WHITESPACE)
+                    ) {
+                    collecting_special = true;
+                    collecting = true;
+                }
+                else if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_WHITESPACE && unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_WHITESPACE) {
+                    collecting_whitespace_lookahead = true;
+                    collecting = true;
+                }
+                else if (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_WHITESPACE) {
+                    split_condition = true;
+                }
+            }
+            else if (!split_condition && collecting) {
+                if (collecting_letter && unicode_cpt_type(utf_char) != CODEPOINT_TYPE_LETTER) {
+                    split_condition = true;
+                }
+                else if (collecting_numeric && unicode_cpt_type(utf_char) != CODEPOINT_TYPE_DIGIT) {
+                    split_condition = true;
+                }
+                else if (collecting_special && (unicode_cpt_type(utf_char) == CODEPOINT_TYPE_LETTER || unicode_cpt_type(utf_char) == CODEPOINT_TYPE_DIGIT || unicode_cpt_type(utf_char) == CODEPOINT_TYPE_WHITESPACE)) {
+                    split_condition = true;
+                }
+                else if (collecting_whitespace_lookahead && (unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_LETTER || unicode_cpt_type(utf_char_next) == CODEPOINT_TYPE_DIGIT)) {
+                    split_condition = true;
+                }
+            }
+
+            if (utf_char_next == "") {
+                split_condition = true; // final
+                token += utf_char;
+            }
+
+            if (split_condition) {
+                if (token.size()) {
+                    bpe_offsets.emplace_back(unicode_cpts_from_utf8(token).size());
+                }
+                token = utf_char;
+                collecting = false;
+                collecting_letter = false;
+                collecting_numeric = false;
+                collecting_special = false;
+                collecting_whitespace_lookahead = false;
+            }
+            else {
+                token += utf_char;
+            }
+        }
+
+        start += offset;
+    }
+
+    return bpe_offsets;
+}
+
+// use std::wregex to split the text
+static std::vector<size_t> unicode_regex_split_stl(const std::wstring & wtext, const std::wstring & regex_expr, const std::vector<size_t> & offsets) {
+    std::wregex expr(regex_expr);
+    std::vector<size_t> bpe_offsets; // store the offset of each word
+    bpe_offsets.reserve(offsets.size()); // Reserve memory for the approximate size
+    size_t start = 0;
+    for (auto offset : offsets) {
+        std::wcregex_iterator it(wtext.data() + start, wtext.data() + start + offset, expr);
+        std::wcregex_iterator end;
+
+        int64_t start_idx = 0;
+        while (it != end) {
+            std::wcmatch match = *it;
+            if (match.position() > start_idx) {
+                bpe_offsets.emplace_back(match.position() - start_idx);
+            }
+            bpe_offsets.emplace_back(match.length());
+            start_idx = match.position() + match.length();
+            ++it;
+        }
+
+        if (start_idx < (int64_t) offset) {
+            bpe_offsets.emplace_back(offset - start_idx);
+        }
+        start += offset;
+    }
+
+    return bpe_offsets;
+}
+
+// use std::regex to split the text
+static std::vector<size_t> unicode_regex_split_stl(const std::string & text, const std::string & regex_expr, const std::vector<size_t> & offsets) {
+    std::regex expr(regex_expr);
+    std::vector<size_t> bpe_offsets; // store the offset of each word
+    bpe_offsets.reserve(offsets.size()); // Reserve memory for the approximate size
+    size_t start = 0;
+    for (auto offset : offsets) {
+        std::cregex_iterator it(text.data() + start, text.data() + start + offset, expr);
+        std::cregex_iterator end;
+
+        int64_t start_idx = 0;
+        while (it != end) {
+            std::cmatch match = *it;
+            if (match.position() > start_idx) {
+                bpe_offsets.emplace_back(match.position() - start_idx);
+            }
+            bpe_offsets.emplace_back(match.length());
+            start_idx = match.position() + match.length();
+            ++it;
+        }
+
+        if (start_idx < (int64_t) offset) {
+            bpe_offsets.emplace_back(offset - start_idx);
+        }
+        start += offset;
+    }
+
+    return bpe_offsets;
+}
+
+static std::vector<size_t> unicode_regex_split_custom(const std::string & text, const std::string & regex_expr, const std::vector<size_t> & offsets) {
+    std::vector<size_t> bpe_offsets;
+
+    (void)(text);
+    (void)(regex_expr);
+    (void)(offsets);
+    // TODO: this implementation is actually wrong, uncomment and run:
+    //       make -j && ./bin/test-tokenizer-0 ../models/ggml-vocab-gpt-2.gguf
+    //if (regex_expr == "'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)") {
+    //    bpe_offsets = unicode_regex_split_custom_gpt2(text, offsets);
+    //}
+
+    return bpe_offsets;
+}
+
 //
 // interface
 //
 
 std::string unicode_cpt_to_utf8(uint32_t cp) {
     std::string result;
+
     if (/* 0x00 <= cp && */ cp <= 0x7f) {
         result.push_back(cp);
+        return result;
     }
-    else if (0x80 <= cp && cp <= 0x7ff) {
+    if (0x80 <= cp && cp <= 0x7ff) {
         result.push_back(0xc0 | ((cp >> 6) & 0x1f));
         result.push_back(0x80 | (cp & 0x3f));
+        return result;
     }
-    else if (0x800 <= cp && cp <= 0xffff) {
+    if (0x800 <= cp && cp <= 0xffff) {
         result.push_back(0xe0 | ((cp >> 12) & 0x0f));
         result.push_back(0x80 | ((cp >> 6) & 0x3f));
         result.push_back(0x80 | (cp & 0x3f));
+        return result;
     }
-    else if (0x10000 <= cp && cp <= 0x10ffff) {
+    if (0x10000 <= cp && cp <= 0x10ffff) {
         result.push_back(0xf0 | ((cp >> 18) & 0x07));
         result.push_back(0x80 | ((cp >> 12) & 0x3f));
         result.push_back(0x80 | ((cp >> 6) & 0x3f));
         result.push_back(0x80 | (cp & 0x3f));
+        return result;
     }
-    else {
-        throw std::invalid_argument("invalid codepoint");
-    }
-    return result;
+
+    throw std::invalid_argument("invalid codepoint");
 }
 
 std::vector<uint32_t> unicode_cpts_normalize_nfd(const std::vector<uint32_t> & cpts) {
@@ -275,3 +520,167 @@ char32_t unicode_tolower(char32_t cp) {
     auto it = unicode_map_lowercase.find(cp);
     return it == unicode_map_lowercase.end() ? cp : it->second;
 }
+
+std::vector<std::string> unicode_regex_split(const std::string & text, const std::vector<std::string> & regex_exprs) {
+    // unicode categories
+    static const std::map<std::string, int> k_ucat_enum = {
+        { "\\p{N}", CODEPOINT_TYPE_DIGIT },
+        { "\\p{L}", CODEPOINT_TYPE_LETTER },
+        { "\\p{P}", CODEPOINT_TYPE_PUNCTUATION },
+    };
+
+    static const std::map<int, int> k_ucat_cpt = {
+        { CODEPOINT_TYPE_DIGIT,         0xD1 },
+        { CODEPOINT_TYPE_LETTER,        0xD2 },
+        { CODEPOINT_TYPE_PUNCTUATION,   0xD3 },
+    };
+
+    static const std::map<int, std::string> k_ucat_map = {
+        { CODEPOINT_TYPE_DIGIT,         "\x30-\x39" }, // 0-9
+        { CODEPOINT_TYPE_LETTER,        "\x41-\x5A\x61-\x7A" }, // A-Za-z
+        { CODEPOINT_TYPE_PUNCTUATION,   "\x21-\x23\x25-\x2A\x2C-\x2F\x3A-\x3B\x3F-\x40\\\x5B-\\\x5D\x5F\\\x7B\\\x7D" }, // !-#%-*,-/:-;?-@\[-\]_\{\}
+    };
+
+    // compute collapsed codepoints only if needed by at least one regex
+    bool need_collapse = false;
+    for (auto & regex_expr : regex_exprs) {
+        // search for unicode categories
+        for (const auto & ucat : k_ucat_enum) {
+            if (std::string::npos != regex_expr.find(ucat.first)) {
+                need_collapse = true;
+                break;
+            }
+        }
+    }
+
+    const auto cpts = unicode_cpts_from_utf8(text);
+
+    // generate a "collapsed" representation of the text, where all codepoints are replaced by a single byte
+    // ref: https://github.com/ggerganov/llama.cpp/pull/6920#issuecomment-2081479935
+    std::string text_collapsed;
+    if (need_collapse) {
+        // collapse all unicode categories
+        text_collapsed.resize(cpts.size());
+
+        for (size_t i = 0; i < cpts.size(); ++i) {
+            // keep single-byte codepoints as is
+            if (cpts[i] < 128) {
+                text_collapsed[i] = cpts[i];
+                continue;
+            }
+
+            const int cpt_type = unicode_cpt_type(cpts[i]);
+
+            if (k_ucat_cpt.find(cpt_type) != k_ucat_cpt.end()) {
+                text_collapsed[i] = k_ucat_cpt.at(cpt_type);
+            } else {
+                text_collapsed[i] = (char) 0xD0; // fallback
+            }
+        }
+    }
+
+    std::vector<size_t> bpe_offsets = { cpts.size() };
+
+    for (auto & regex_expr : regex_exprs) {
+        // first, see if we have an efficient custom regex implementation
+        auto tmp = unicode_regex_split_custom(text, regex_expr, bpe_offsets);
+
+        if (!tmp.empty()) {
+            bpe_offsets = std::move(tmp);
+            continue;
+        }
+
+        // fallback to general-purpose std::regex / std::wregex
+        try {
+            // if a unicode category is used in the regex, we use the collapsed text and replace the unicode category
+            // with the corresponding collapsed representation
+            bool use_collapsed = false;
+            for (auto & ucat : k_ucat_enum) {
+                if (std::string::npos != regex_expr.find(ucat.first)) {
+                    use_collapsed = true;
+                    break;
+                }
+            }
+
+            if (use_collapsed) {
+                // sanity-check that the original regex does not contain any non-ASCII characters
+                const auto cpts_regex = unicode_cpts_from_utf8(regex_expr);
+                for (size_t i = 0; i < cpts_regex.size(); ++i) {
+                    if (cpts_regex[i] >= 128) {
+                        throw std::runtime_error("Regex includes both unicode categories and non-ASCII characters - not supported");
+                    }
+                }
+
+                // generate a collapsed representation of the regex
+                std::string regex_expr_collapsed;
+
+                // track if we are inside [], because nested [] are not allowed
+                bool inside = false;
+                for (size_t i = 0; i < regex_expr.size(); ++i) {
+                    if (regex_expr[i] == '[' && (i == 0 || regex_expr[i - 1] != '\\')) {
+                        regex_expr_collapsed += '[';
+                        inside = true;
+                        continue;
+                    }
+
+                    if (inside && regex_expr[i] == ']' && regex_expr[i - 1] != '\\') {
+                        regex_expr_collapsed += ']';
+                        inside = false;
+                        continue;
+                    }
+
+                    if (regex_expr[i + 0] == '\\' && i + 4 < regex_expr.size() &&
+                        regex_expr[i + 1] == 'p' &&
+                        regex_expr[i + 2] == '{' &&
+                        regex_expr[i + 4] == '}') {
+                        const std::string pat = regex_expr.substr(i, 5);
+                        if (k_ucat_enum.find(pat) != k_ucat_enum.end()) {
+                            if (!inside) {
+                                regex_expr_collapsed += '[';
+                            }
+                            regex_expr_collapsed += k_ucat_cpt.at(k_ucat_enum.at(pat));
+                            regex_expr_collapsed += k_ucat_map.at(k_ucat_enum.at(pat));
+                            if (!inside) {
+                                regex_expr_collapsed += ']';
+                            }
+                            i += 4;
+                            continue;
+                        }
+                    }
+
+                    regex_expr_collapsed += regex_expr[i];
+                }
+
+                //printf("text_collapsed: %s\n", text_collapsed.c_str());
+                //printf("regex_expr_collapsed: %s\n", regex_expr_collapsed.c_str());
+                bpe_offsets = unicode_regex_split_stl(text_collapsed, regex_expr_collapsed, bpe_offsets);
+            } else {
+                // no unicode category used, we can use std::wregex directly
+                const std::wstring wtext       = unicode_wstring_from_utf8(text);
+                const std::wstring wregex_expr = unicode_wstring_from_utf8(regex_expr);
+
+                //printf("text: %s\n", text.c_str());
+                //printf("regex_expr: %s\n", regex_expr.c_str());
+                bpe_offsets = unicode_regex_split_stl(wtext, wregex_expr, bpe_offsets);
+            }
+        } catch (std::regex_error & e) {
+            fprintf(stderr, "Failed to process regex: '%s'\n", regex_expr.c_str());
+            fprintf(stderr, "Regex error: %s\n", e.what());
+            throw std::runtime_error("Failed to process regex");
+        }
+    }
+
+    std::vector<std::string> bpe_words;
+    bpe_words.reserve(bpe_offsets.size()); // reserve memory for the approximate size
+
+    size_t start = 0;
+    for (size_t & offset : bpe_offsets) {
+        bpe_words.emplace_back();
+        for (size_t i = start; i < start + offset; ++i) {
+            bpe_words.back() += unicode_cpt_to_utf8(cpts[i]);
+        }
+        start += offset;
+    }
+
+    return unicode_byte_encoding_process(bpe_words);
+}
diff --git a/unicode.h b/unicode.h
index 6a0be393a46b40..ce2bcef5a24b1f 100644
--- a/unicode.h
+++ b/unicode.h
@@ -24,5 +24,6 @@ int unicode_cpt_type(const std::string & utf8);
 std::string unicode_byte_to_utf8(uint8_t byte);
 uint8_t unicode_utf8_to_byte(const std::string & utf8);
 
-// simple tolower that only implements one-to-one mapping, not one-to-many
 char32_t unicode_tolower(char32_t cp);
+
+std::vector<std::string> unicode_regex_split(const std::string & text, const std::vector<std::string> & regex_exprs);