Modelz LLM is an inference server that facilitates the utilization of open source large language models (LLMs), such as FastChat, LLaMA, and ChatGLM, on either local or cloud-based environments with OpenAI compatible API.
- OpenAI compatible API: Modelz LLM provides an OpenAI compatible API for LLMs, which means you can use the OpenAI python SDK or LangChain to interact with the model.
- Self-hosted: Modelz LLM can be easily deployed on either local or cloud-based environments.
- Open source LLMs: Modelz LLM supports open source LLMs, such as FastChat, LLaMA, and ChatGLM.
- Cloud native: We provide docker images for different LLMs, which can be easily deployed on Kubernetes, or other cloud-based environments (e.g. Modelz)
pip install modelz-llm
# or install from source
pip install git+https://github.com/tensorchord/modelz-llm.git[gpu]Please first start the self-hosted API server by following the instructions:
modelz-llm -m bigscience/bloomz-560m --device cpuCurrently, we support the following models:
| Model Name | Huggingface Model | Docker Image | Recommended GPU |
|---|---|---|---|
| FastChat T5 | lmsys/fastchat-t5-3b-v1.0 |
modelzai/llm-fastchat-t5-3b | Nvidia L4(24GB) |
| Vicuna 7B Delta V1.1 | lmsys/vicuna-7b-delta-v1.1 |
modelzai/llm-vicuna-7b | Nvidia A100(40GB) |
| LLaMA 7B | decapoda-research/llama-7b-hf |
modelzai/llm-llama-7b | Nvidia A100(40GB) |
| ChatGLM 6B INT4 | THUDM/chatglm-6b-int4 |
modelzai/llm-chatglm-6b-int4 | Nvidia T4(16GB) |
| ChatGLM 6B | THUDM/chatglm-6b |
modelzai/llm-chatglm-6b | Nvidia L4(24GB) |
| Bloomz 560M | bigscience/bloomz-560m |
modelzai/llm-bloomz-560m | CPU |
| Bloomz 1.7B | bigscience/bloomz-1b7 |
CPU | |
| Bloomz 3B | bigscience/bloomz-3b |
Nvidia L4(24GB) | |
| Bloomz 7.1B | bigscience/bloomz-7b1 |
Nvidia A100(40GB) |
Then you can use the OpenAI python SDK to interact with the model:
import openai
openai.api_base="http://localhost:8000"
openai.api_key="any"
# create a chat completion
chat_completion = openai.ChatCompletion.create(model="any", messages=[{"role": "user", "content": "Hello world"}])You could also integrate modelz-llm with langchain:
import openai
openai.api_base="http://localhost:8000"
openai.api_key="any"
from langchain.llms import OpenAI
llm = OpenAI()
llm.generate(prompts=["Could you please recommend some movies?"])You could also deploy the modelz-llm directly on Modelz:
Modelz LLM supports the following APIs for interacting with open source large language models:
/completions/chat/completions/embeddings/engines/<any>/embeddings/v1/completions/v1/chat/completions/v1/embeddings
