How to use devingulliver/mamba-gguf with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf devingulliver/mamba-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf devingulliver/mamba-gguf:Q4_K_M
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf devingulliver/mamba-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf devingulliver/mamba-gguf:Q4_K_M
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 devingulliver/mamba-gguf:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf devingulliver/mamba-gguf:Q4_K_M
docker model run hf.co/devingulliver/mamba-gguf:Q4_K_M
How to use devingulliver/mamba-gguf with vLLM:
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "devingulliver/mamba-gguf" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "devingulliver/mamba-gguf", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'
How to use devingulliver/mamba-gguf with Ollama:
ollama run hf.co/devingulliver/mamba-gguf:Q4_K_M
How to use devingulliver/mamba-gguf with Docker Model Runner:
How to use devingulliver/mamba-gguf with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull devingulliver/mamba-gguf:Q4_K_M
lemonade run user.mamba-gguf-Q4_K_M
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