Instructions to use shaowenchen/baichuan2-7b-chat-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use shaowenchen/baichuan2-7b-chat-gguf with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf shaowenchen/baichuan2-7b-chat-gguf:Q4_K_S
# Run inference directly in the terminal:
llama cli -hf shaowenchen/baichuan2-7b-chat-gguf:Q4_K_S

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf shaowenchen/baichuan2-7b-chat-gguf:Q4_K_S
# Run inference directly in the terminal:
llama cli -hf shaowenchen/baichuan2-7b-chat-gguf:Q4_K_S

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf shaowenchen/baichuan2-7b-chat-gguf:Q4_K_S
# Run inference directly in the terminal:
./llama-cli -hf shaowenchen/baichuan2-7b-chat-gguf:Q4_K_S

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf shaowenchen/baichuan2-7b-chat-gguf:Q4_K_S
# Run inference directly in the terminal:
./build/bin/llama-cli -hf shaowenchen/baichuan2-7b-chat-gguf:Q4_K_S

Use Docker

docker model run hf.co/shaowenchen/baichuan2-7b-chat-gguf:Q4_K_S

LM Studio
Jan

vLLM

How to use shaowenchen/baichuan2-7b-chat-gguf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "shaowenchen/baichuan2-7b-chat-gguf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "shaowenchen/baichuan2-7b-chat-gguf",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/shaowenchen/baichuan2-7b-chat-gguf:Q4_K_S

Ollama
How to use shaowenchen/baichuan2-7b-chat-gguf with Ollama:
```
ollama run hf.co/shaowenchen/baichuan2-7b-chat-gguf:Q4_K_S
```
Unsloth Desktop
Docker Model Runner
How to use shaowenchen/baichuan2-7b-chat-gguf with Docker Model Runner:
```
docker model run hf.co/shaowenchen/baichuan2-7b-chat-gguf:Q4_K_S
```

Lemonade

How to use shaowenchen/baichuan2-7b-chat-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull shaowenchen/baichuan2-7b-chat-gguf:Q4_K_S

Run and chat with the model

lemonade run user.baichuan2-7b-chat-gguf-Q4_K_S

List all available models

lemonade list

Atomic Chat

想使用llama.cpp运行，请问需要怎么设置参数呢

by zhaogx - opened Oct 18, 2023

Discussion

zhaogx

Oct 18, 2023

•

edited Oct 18, 2023

想使用llama.cpp运行，请问需要怎么设置参数呢。我是搞java后台开发的AI小白，问题可能有些简单了，麻烦了

shaowenchen

Owner Oct 27, 2023

想使用llama.cpp运行，请问需要怎么设置参数呢。我是搞java后台开发的AI小白，问题可能有些简单了，麻烦了
可以直接用 docker 版本比较简单，如果想使用命令行，需要编译之后 ./main -m /Users/shaowenchen/Code/HuggingFace/Baichuan-13B-Chat-GGUF/Baichuan-13B-Chat-f16-q4_0.gguf -p "hi" -n 2048 这样就可以运行本地测试了

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