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eugenehp
/
chatterbox

Text-to-Speech
ONNX
GGUF
Chatterbox
rlx
tts
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Chatterbox

    How to use eugenehp/chatterbox with Chatterbox:

    # pip install chatterbox-tts
    import torchaudio as ta
    from chatterbox.tts import ChatterboxTTS
    
    model = ChatterboxTTS.from_pretrained(device="cuda")
    
    text = "Ezreal and Jinx teamed up with Ahri, Yasuo, and Teemo to take down the enemy's Nexus in an epic late-game pentakill."
    wav = model.generate(text)
    ta.save("test-1.wav", wav, model.sr)
    
    # If you want to synthesize with a different voice, specify the audio prompt
    AUDIO_PROMPT_PATH="YOUR_FILE.wav"
    wav = model.generate(text, audio_prompt_path=AUDIO_PROMPT_PATH)
    ta.save("test-2.wav", wav, model.sr)
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • llama.cpp

    How to use eugenehp/chatterbox 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 eugenehp/chatterbox:Q4_K_M
    # Run inference directly in the terminal:
    llama cli -hf eugenehp/chatterbox:Q4_K_M
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf eugenehp/chatterbox:Q4_K_M
    # Run inference directly in the terminal:
    llama cli -hf eugenehp/chatterbox:Q4_K_M
    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 eugenehp/chatterbox:Q4_K_M
    # Run inference directly in the terminal:
    ./llama-cli -hf eugenehp/chatterbox:Q4_K_M
    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 eugenehp/chatterbox:Q4_K_M
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf eugenehp/chatterbox:Q4_K_M
    Use Docker
    docker model run hf.co/eugenehp/chatterbox:Q4_K_M
  • LM Studio
  • Jan
  • Ollama

    How to use eugenehp/chatterbox with Ollama:

    ollama run hf.co/eugenehp/chatterbox:Q4_K_M
  • Unsloth Studio

    How to use eugenehp/chatterbox 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 eugenehp/chatterbox 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 eugenehp/chatterbox to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for eugenehp/chatterbox to start chatting
  • Docker Model Runner

    How to use eugenehp/chatterbox with Docker Model Runner:

    docker model run hf.co/eugenehp/chatterbox:Q4_K_M
  • Lemonade

    How to use eugenehp/chatterbox with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull eugenehp/chatterbox:Q4_K_M
    Run and chat with the model
    lemonade run user.chatterbox-Q4_K_M
    List all available models
    lemonade list
  • Atomic Chat
chatterbox
4.72 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 5 commits
eugenehp's picture
eugenehp
Upload folder using huggingface_hub
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  • native
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  • .gitattributes
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  • LICENSE
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  • README.md
    1.94 kB
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  • config.json
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  • default_voice.wav
    714 kB
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  • generation_config.json
    93 Bytes
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  • manifest.json
    255 Bytes
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  • preprocessor_config.json
    130 Bytes
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  • t3-q4_k_m.gguf
    314 MB
    xet
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  • tokenizer.json
    28.5 kB
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  • tokenizer_config.json
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  • weights.safetensors
    81.4 MB
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