Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Hardware
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

failspy
/
Meta-Llama-3-8B-Instruct-abliterated-v3-GGUF

Transformers
GGUF
conversational
Model card Files Files and versions
xet
Community

Instructions to use failspy/Meta-Llama-3-8B-Instruct-abliterated-v3-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use failspy/Meta-Llama-3-8B-Instruct-abliterated-v3-GGUF with Transformers:

    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("failspy/Meta-Llama-3-8B-Instruct-abliterated-v3-GGUF", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • llama.cpp

    How to use failspy/Meta-Llama-3-8B-Instruct-abliterated-v3-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 failspy/Meta-Llama-3-8B-Instruct-abliterated-v3-GGUF
    # Run inference directly in the terminal:
    llama cli -hf failspy/Meta-Llama-3-8B-Instruct-abliterated-v3-GGUF
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf failspy/Meta-Llama-3-8B-Instruct-abliterated-v3-GGUF
    # Run inference directly in the terminal:
    llama cli -hf failspy/Meta-Llama-3-8B-Instruct-abliterated-v3-GGUF
    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 failspy/Meta-Llama-3-8B-Instruct-abliterated-v3-GGUF
    # Run inference directly in the terminal:
    ./llama-cli -hf failspy/Meta-Llama-3-8B-Instruct-abliterated-v3-GGUF
    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 failspy/Meta-Llama-3-8B-Instruct-abliterated-v3-GGUF
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf failspy/Meta-Llama-3-8B-Instruct-abliterated-v3-GGUF
    Use Docker
    docker model run hf.co/failspy/Meta-Llama-3-8B-Instruct-abliterated-v3-GGUF
  • LM Studio
  • Jan
  • Ollama

    How to use failspy/Meta-Llama-3-8B-Instruct-abliterated-v3-GGUF with Ollama:

    ollama run hf.co/failspy/Meta-Llama-3-8B-Instruct-abliterated-v3-GGUF
  • Unsloth Desktop
  • Docker Model Runner

    How to use failspy/Meta-Llama-3-8B-Instruct-abliterated-v3-GGUF with Docker Model Runner:

    docker model run hf.co/failspy/Meta-Llama-3-8B-Instruct-abliterated-v3-GGUF
  • Lemonade

    How to use failspy/Meta-Llama-3-8B-Instruct-abliterated-v3-GGUF with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull failspy/Meta-Llama-3-8B-Instruct-abliterated-v3-GGUF
    Run and chat with the model
    lemonade run user.Meta-Llama-3-8B-Instruct-abliterated-v3-GGUF-{{QUANT_TAG}}
    List all available models
    lemonade list
  • Atomic Chat
Meta-Llama-3-8B-Instruct-abliterated-v3-GGUF
45.9 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 10 commits
failspy's picture
failspy
Upload folder using huggingface_hub
f969783 verified over 2 years ago
  • .gitattributes
    2.02 kB
    Upload folder using huggingface_hub over 2 years ago
  • Meta-Llama-3-8B-Instruct-abliterated-v3.gguf
    16.1 GB
    xet
    Upload folder using huggingface_hub over 2 years ago
  • Meta-Llama-3-8B-Instruct-abliterated-v3_q3.gguf
    4.02 GB
    xet
    Upload folder using huggingface_hub over 2 years ago
  • Meta-Llama-3-8B-Instruct-abliterated-v3_q4.gguf
    4.92 GB
    xet
    Upload folder using huggingface_hub over 2 years ago
  • Meta-Llama-3-8B-Instruct-abliterated-v3_q5.gguf
    5.73 GB
    xet
    Upload folder using huggingface_hub over 2 years ago
  • Meta-Llama-3-8B-Instruct-abliterated-v3_q6.gguf
    6.6 GB
    xet
    Upload folder using huggingface_hub over 2 years ago
  • Meta-Llama-3-8B-Instruct-abliterated-v3_q8.gguf
    8.54 GB
    xet
    Upload folder using huggingface_hub over 2 years ago
  • README.md
    5.2 kB
    Create README.md over 2 years ago