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andykcheng
/
tv_remote_gguf

Transformers
GGUF
English
llama
text-generation-inference
unsloth
conversational
Model card Files Files and versions
xet
Community

Instructions to use andykcheng/tv_remote_gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use andykcheng/tv_remote_gguf with Transformers:

    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("andykcheng/tv_remote_gguf", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • llama.cpp

    How to use andykcheng/tv_remote_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 andykcheng/tv_remote_gguf:Q8_0
    # Run inference directly in the terminal:
    llama cli -hf andykcheng/tv_remote_gguf:Q8_0
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf andykcheng/tv_remote_gguf:Q8_0
    # Run inference directly in the terminal:
    llama cli -hf andykcheng/tv_remote_gguf:Q8_0
    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 andykcheng/tv_remote_gguf:Q8_0
    # Run inference directly in the terminal:
    ./llama-cli -hf andykcheng/tv_remote_gguf:Q8_0
    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 andykcheng/tv_remote_gguf:Q8_0
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf andykcheng/tv_remote_gguf:Q8_0
    Use Docker
    docker model run hf.co/andykcheng/tv_remote_gguf:Q8_0
  • LM Studio
  • Jan
  • Ollama

    How to use andykcheng/tv_remote_gguf with Ollama:

    ollama run hf.co/andykcheng/tv_remote_gguf:Q8_0
  • Unsloth Studio

    How to use andykcheng/tv_remote_gguf with Unsloth Studio:

    Install Unsloth Studio (macOS, Linux, WSL)
    curl -fsSL https://unsloth.ai/install.sh | sh
    # Run unsloth studio
    unsloth studio -H 0.0.0.0 -p 8888
    # Then open http://localhost:8888 in your browser
    # Search for andykcheng/tv_remote_gguf to start chatting
    Install Unsloth Studio (Windows)
    irm https://unsloth.ai/install.ps1 | iex
    # Run unsloth studio
    unsloth studio -H 0.0.0.0 -p 8888
    # Then open http://localhost:8888 in your browser
    # Search for andykcheng/tv_remote_gguf to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for andykcheng/tv_remote_gguf to start chatting
  • Docker Model Runner

    How to use andykcheng/tv_remote_gguf with Docker Model Runner:

    docker model run hf.co/andykcheng/tv_remote_gguf:Q8_0
  • Lemonade

    How to use andykcheng/tv_remote_gguf with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull andykcheng/tv_remote_gguf:Q8_0
    Run and chat with the model
    lemonade run user.tv_remote_gguf-Q8_0
    List all available models
    lemonade list
  • Atomic Chat
tv_remote_gguf
8.54 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 6 commits
andykcheng's picture
andykcheng
(Trained with Unsloth)
b8ec5fd verified about 2 years ago
  • .gitattributes
    1.57 kB
    (Trained with Unsloth) about 2 years ago
  • Modelfile
    421 Bytes
    (Trained with Unsloth) about 2 years ago
  • README.md
    610 Bytes
    Upload README.md with huggingface_hub about 2 years ago
  • config.json
    29 Bytes
    (Trained with Unsloth) about 2 years ago
  • unsloth.Q8_0.gguf
    8.54 GB
    xet
    (Trained with Unsloth) about 2 years ago