Instructions to use MLDataScientist/Mistral-Large-Instruct-2407-GPTQ-3bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps
- vLLM
How to use MLDataScientist/Mistral-Large-Instruct-2407-GPTQ-3bit with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "MLDataScientist/Mistral-Large-Instruct-2407-GPTQ-3bit" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "MLDataScientist/Mistral-Large-Instruct-2407-GPTQ-3bit", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/MLDataScientist/Mistral-Large-Instruct-2407-GPTQ-3bit
- SGLang
How to use MLDataScientist/Mistral-Large-Instruct-2407-GPTQ-3bit with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "MLDataScientist/Mistral-Large-Instruct-2407-GPTQ-3bit" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "MLDataScientist/Mistral-Large-Instruct-2407-GPTQ-3bit", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "MLDataScientist/Mistral-Large-Instruct-2407-GPTQ-3bit" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "MLDataScientist/Mistral-Large-Instruct-2407-GPTQ-3bit", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use MLDataScientist/Mistral-Large-Instruct-2407-GPTQ-3bit with Docker Model Runner:
docker model run hf.co/MLDataScientist/Mistral-Large-Instruct-2407-GPTQ-3bit
3bit QPTQ quants for Mistral-Large-Instruct-2411
Do you by any chance have the 3 bit quants for the newer version of Mistral-Large-Instruct-2411
I have 2 x MI100 with 64GB VRAM total and there are only GGUF quants available which would fit my setup.
But they are slow with vLLM especially in batched mode.
Hello @dazipe ,
Unfortunately, no. I only converted 2407 since it had better benchmark scores in HumanEval and live bench. I Also have 2xMI60 and I converted this model using vast.ai for $20. It takes around 20h to convert but the result and performance are great.