From c93655c0a3bd8d9c2b66f85bacc174ceb81de79f Mon Sep 17 00:00:00 2001
From: Jan Philipp Harries <2862336+jphme@users.noreply.github.com>
Date: Sat, 5 Aug 2023 20:16:41 +0200
Subject: [PATCH] Added Orca Mini prompt strategy (#263)

* added Orca Mini prompt strategy

* maybe this fixed precommit errors?

* pre-commits passing

---------

Co-authored-by: Jan Philipp Harries <jpdus@users.noreply.github.com>
---
 src/axolotl/prompt_strategies/orcamini.py | 46 +++++++++++++++++++++++
 1 file changed, 46 insertions(+)
 create mode 100644 src/axolotl/prompt_strategies/orcamini.py

diff --git a/src/axolotl/prompt_strategies/orcamini.py b/src/axolotl/prompt_strategies/orcamini.py
new file mode 100644
index 000000000..04ce5767d
--- /dev/null
+++ b/src/axolotl/prompt_strategies/orcamini.py
@@ -0,0 +1,46 @@
+"""
+Prompt Strategy for finetuning Orca Mini (v2) models
+see also https://huggingface.co/psmathur/orca_mini_v2_7b for more information
+
+Use dataset type: orcamini in conig.yml to use this prompt style.
+
+Compared to the alpaca_w_system.open_orca dataset type,
+this one specifies the system prompt with "### System:".
+
+Not suited/tested for multiple-turn conversations without further adjustments.
+"""
+from typing import Generator, Union
+
+from axolotl.prompt_strategies.alpaca_w_system import OpenOrcaPromptTokenizingStrategy
+from axolotl.prompters import AlpacaPrompter
+
+
+class OrcaMiniPrompter(AlpacaPrompter):
+    """Adjusted Prompter for Orca Mini (v2) datasets"""
+
+    def match_prompt_style(self):
+        self.turn_no_input_format = (
+            "### System:\n{system}\n\n### User:\n{instruction}\n\n### Response:\n"
+        )
+
+    def build_prompt_w_system(
+        self,
+        system: str,
+        instruction: str,
+        output: Union[None, str] = None,
+    ) -> Generator[str, None, None]:
+        # returns the full prompt from instruction and optional input
+        # if a label (=response, =output) is provided, it's also appended.
+        res = self.turn_no_input_format.format(system=system, instruction=instruction)
+        if output:
+            res = f"{res}{output}"
+        yield res
+
+
+def load(tokenizer, cfg):
+    return OpenOrcaPromptTokenizingStrategy(
+        OrcaMiniPrompter(),
+        tokenizer,
+        cfg.train_on_inputs,
+        cfg.sequence_len,
+    )