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itod/
mistral-7B-instruct-v0.2-q8

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Source Mistral 7B model:
https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2/
This model is converted from Bfloat16 datatype to Int8 datatype with convert tool from:
https://github.com/ggerganov/llama.cpp
Deployment on CPU:
Pull the ready-made llama.cpp container:

docker pull ghcr.io/ggerganov/llama.cpp:server

Assuming mistral-7B-instruct-v0.2-q8.gguf file is downloaded to /path/to/models directory on local machine, run the container accesing the model with:

docker run -v /path/to/models:/models -p 8000:8000 ghcr.io/ggerganov/llama.cpp:server -m /models/istral-7B-instruct-v0.2-q8.gguf --port 8000 --host 0.0.0.0 -n 512

Test the deployment accessing the model with the browser at http://localhost:8000
llama.cpp server also provides OpenAI compatible API
Deployment on CUDA GPU:

docker pull ghcr.io/ggerganov/llama.cpp:server-cuda

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-q8.gguf --port 8000 --host 0.0.0.0 -n 512 --n-gpu-layers 50

If CUDA GPU with 16GB RAM is available, the version of the model converted to float16 may be interesting, available in this repo:
https://huggingface.co/itod/mistral-7B-instruct-v0.2-f16
More details about usage is avalable in llama.cpp documentation:
https://github.com/ggerganov/llama.cpp/tree/master/examples/server

itod/mistral-7B-instruct-v0.2-q8

itod/
mistral-7B-instruct-v0.2-q8