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How to use from
llama.cppInstall from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Diluzx/Mistral-Nemo-Base-2407:F16# Run inference directly in the terminal:
llama cli -hf Diluzx/Mistral-Nemo-Base-2407:F16Build from source code
git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf Diluzx/Mistral-Nemo-Base-2407:F16# Run inference directly in the terminal:
./build/bin/llama cli -hf Diluzx/Mistral-Nemo-Base-2407:F16Use Docker
docker model run hf.co/Diluzx/Mistral-Nemo-Base-2407:F16Quick Links
Uploaded model
- Developed by: Diluzx
- License: apache-2.0
- Finetuned from model : unsloth/Mistral-Nemo-Base-2407-bnb-4bit
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
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Model tree for Diluzx/Mistral-Nemo-Base-2407
Base model
unsloth/Mistral-Nemo-Base-2407-bnb-4bit
Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf Diluzx/Mistral-Nemo-Base-2407:F16# Run inference directly in the terminal: llama cli -hf Diluzx/Mistral-Nemo-Base-2407:F16