The Baichuan2-13B-Chat model is a 13B Large Language Model (LLM) developed by Baichuan Intelligent, which is inspired by offline reinforcement learning. According to the team, this approach allows the model to learn from mixed-quality data without preference labels, enabling it to deliver exceptional performance that rivals even the sophisticated ChatGPT models.
In this article, we will cover
- How to run Baichuan2-13B-Chat on your own device
- How to create an OpenAI-compatible API service for Baichuan2-13B-Chat
We will use the Rust + Wasm stack to develop and deploy applications for this model. There are no complex Python packages or C++ toolchains to install! See why we choose this tech stack.
Run the model on your own device
Step 1: Install WasmEdge via the following command line.
curl -sSf https://raw.githubusercontent.com/WasmEdge/WasmEdge/master/utils/install.sh | bash -s -- --plugins wasmedge_rustls wasi_nn-ggml
Step 2: Download the model GGUF file. It may take a long time, since the size of the model is several GBs.
curl -LO https://huggingface.co/second-state/Baichuan2-13B-Chat-GGUF/resolve/main/Baichuan2-13B-Chat-ggml-model-q4_0.gguf
Step 3: Download a cross-platform portable Wasm file for the chat app. The application allows you to chat with the model on the command line. The Rust source code for the app is here.
curl -LO https://github.com/LlamaEdge/LlamaEdge/releases/latest/download/llama-chat.wasm
That's it. You can chat with the model in the terminal by entering the following command.
wasmedge --dir .:. --nn-preload default:GGML:AUTO:Baichuan2-13B-Chat-ggml-model-q4_0.gguf llama-chat.wasm -p baichuan-2 -r '用户:'
The portable Wasm app automatically takes advantage of the hardware accelerators (eg GPUs) I have on the device.
On my Mac M1 32G memory device, it clocks in at about 7.85 tokens per second.
[USER]:一个苹果5元钱，2个苹果多少钱？
[ASSITANT]:两个苹果需要支付10元钱。
[USER]:
Create an OpenAI-compatible API service
An OpenAI-compatible web API allows the model to work with a large ecosystem of LLM tools and agent frameworks such as flows.network, LangChain and LlamaIndex.
Download an API server app. It is also a cross-platform portable Wasm app that can run on many CPU and GPU devices.
curl -LO https://github.com/LlamaEdge/LlamaEdge/releases/latest/download/llama-api-server.wasm
Then, use the following command lines to start an API server for the model.
wasmedge --dir .:. --nn-preload default:GGML:AUTO:Baichuan2-13B-Chat-ggml-model-q4_0.gguf llama-api-server.wasm -p baichuan-2
From another terminal, you can interact with the API server using curl.
curl -X POST http://0.0.0.0:8080/v1/chat/completions -H 'accept:application/json' -H 'Content-Type: application/json' -d '{"messages":[{"role":"system", "content":"You are a helpful AI assistant"}, {"role":"user", "content":"中国的四大名著是什么？"}], "model":"Baichuan2-13B"}'
That’s all. WasmEdge is the easiest, fastest, and safest way to run LLM applications. Give it a try!
Join the WasmEdge discord to ask questions or share insights.
No time to DIY? Book a Demo with us to enjoy your own LLMs across devices!