Instructions to use cortexso/mixtral with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use cortexso/mixtral 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 cortexso/mixtral # Run inference directly in the terminal: llama cli -hf cortexso/mixtral
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf cortexso/mixtral # Run inference directly in the terminal: llama cli -hf cortexso/mixtral
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 cortexso/mixtral # Run inference directly in the terminal: ./llama-cli -hf cortexso/mixtral
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 cortexso/mixtral # Run inference directly in the terminal: ./build/bin/llama-cli -hf cortexso/mixtral
Use Docker
docker model run hf.co/cortexso/mixtral
- LM Studio
- Jan
- Ollama
How to use cortexso/mixtral with Ollama:
ollama run hf.co/cortexso/mixtral
- Unsloth Desktop
- Docker Model Runner
How to use cortexso/mixtral with Docker Model Runner:
docker model run hf.co/cortexso/mixtral
- Lemonade
How to use cortexso/mixtral with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull cortexso/mixtral
Run and chat with the model
lemonade run user.mixtral-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
Update model.yml
Browse files
model.yml
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@@ -15,5 +15,5 @@ stream: true # true | false
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# Engine / Model Settings
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ngl: 33 # Infer from base config.json -> num_attention_heads
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ctx_len: 32768 # Infer from base config.json -> max_position_embeddings
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engine:
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prompt_template: "[INST] {prompt} [/INST]"
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# Engine / Model Settings
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ngl: 33 # Infer from base config.json -> num_attention_heads
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ctx_len: 32768 # Infer from base config.json -> max_position_embeddings
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engine: llama-cpp
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prompt_template: "[INST] {prompt} [/INST]"
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