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from-our-page
/
Trinity-Nano-Base-Pre-Anneal-Q6_K-Imatrix-GGUF

Text Generation
GGUF
imatrix
q6_k
Model card Files Files and versions
xet
Community

Instructions to use from-our-page/Trinity-Nano-Base-Pre-Anneal-Q6_K-Imatrix-GGUF 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 from-our-page/Trinity-Nano-Base-Pre-Anneal-Q6_K-Imatrix-GGUF 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 from-our-page/Trinity-Nano-Base-Pre-Anneal-Q6_K-Imatrix-GGUF:Q6_K
    # Run inference directly in the terminal:
    llama cli -hf from-our-page/Trinity-Nano-Base-Pre-Anneal-Q6_K-Imatrix-GGUF:Q6_K
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf from-our-page/Trinity-Nano-Base-Pre-Anneal-Q6_K-Imatrix-GGUF:Q6_K
    # Run inference directly in the terminal:
    llama cli -hf from-our-page/Trinity-Nano-Base-Pre-Anneal-Q6_K-Imatrix-GGUF:Q6_K
    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 from-our-page/Trinity-Nano-Base-Pre-Anneal-Q6_K-Imatrix-GGUF:Q6_K
    # Run inference directly in the terminal:
    ./llama-cli -hf from-our-page/Trinity-Nano-Base-Pre-Anneal-Q6_K-Imatrix-GGUF:Q6_K
    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 from-our-page/Trinity-Nano-Base-Pre-Anneal-Q6_K-Imatrix-GGUF:Q6_K
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf from-our-page/Trinity-Nano-Base-Pre-Anneal-Q6_K-Imatrix-GGUF:Q6_K
    Use Docker
    docker model run hf.co/from-our-page/Trinity-Nano-Base-Pre-Anneal-Q6_K-Imatrix-GGUF:Q6_K
  • LM Studio
  • Jan
  • vLLM

    How to use from-our-page/Trinity-Nano-Base-Pre-Anneal-Q6_K-Imatrix-GGUF with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "from-our-page/Trinity-Nano-Base-Pre-Anneal-Q6_K-Imatrix-GGUF"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "from-our-page/Trinity-Nano-Base-Pre-Anneal-Q6_K-Imatrix-GGUF",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/from-our-page/Trinity-Nano-Base-Pre-Anneal-Q6_K-Imatrix-GGUF:Q6_K
  • Ollama

    How to use from-our-page/Trinity-Nano-Base-Pre-Anneal-Q6_K-Imatrix-GGUF with Ollama:

    ollama run hf.co/from-our-page/Trinity-Nano-Base-Pre-Anneal-Q6_K-Imatrix-GGUF:Q6_K
  • Unsloth Desktop
  • Docker Model Runner

    How to use from-our-page/Trinity-Nano-Base-Pre-Anneal-Q6_K-Imatrix-GGUF with Docker Model Runner:

    docker model run hf.co/from-our-page/Trinity-Nano-Base-Pre-Anneal-Q6_K-Imatrix-GGUF:Q6_K
  • Lemonade

    How to use from-our-page/Trinity-Nano-Base-Pre-Anneal-Q6_K-Imatrix-GGUF with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull from-our-page/Trinity-Nano-Base-Pre-Anneal-Q6_K-Imatrix-GGUF:Q6_K
    Run and chat with the model
    lemonade run user.Trinity-Nano-Base-Pre-Anneal-Q6_K-Imatrix-GGUF-Q6_K
    List all available models
    lemonade list
  • Atomic Chat
Trinity-Nano-Base-Pre-Anneal-Q6_K-Imatrix-GGUF
5.05 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 4 commits
mesh-ops's picture
mesh-ops
Upload README.md with huggingface_hub
27a1240 verified 9 months ago
  • .gitattributes
    1.59 kB
    Upload Trinity-Nano-Base-Pre-Anneal.Q6_K.gguf with huggingface_hub 9 months ago
  • README.md
    3.21 kB
    Upload README.md with huggingface_hub 9 months ago
  • Trinity-Nano-Base-Pre-Anneal.Q6_K.gguf
    5.05 GB
    xet
    Upload Trinity-Nano-Base-Pre-Anneal.Q6_K.gguf with huggingface_hub 9 months ago