- Source Mistral 7B model:
https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2/ - This model is converted from Bfloat16 datatype to Float16 datatype with convert tool from:
https://github.com/ggerganov/llama.cpp - Deployment on CUDA GPU:
Pull the ready-made llama.cpp container:
docker pull ghcr.io/ggerganov/llama.cpp:server-cuda
Assuming mistral-7B-instruct-v0.2-fp16.gguf file is downloaded to /path/to/models directory on the local machine, run the container accesing the model with:
docker run --gpus all -v /path/to/models:/models -p 8000:8000 ghcr.io/ggerganov/llama.cpp:server-cuda -m /models/mistral-7B-instruct-v0.2-fp16.gguf --port 8000 --host 0.0.0.0 -n 512 --n-gpu-layers 50
- Test the deployment accessing the model with the browser at http://localhost:8000
- llama.cpp server also provides OpenAI compatible API
- If CUDA GPU is not available, the version of the model converted to int8 may be interesting, available in this repo:
https://huggingface.co/itod/mistral-7B-instruct-v0.2-q8 - More details about usage is avalable in llama.cpp documentation:
https://github.com/ggerganov/llama.cpp/tree/master/examples/server
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