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agkavin
/
Avatar-Speech

Diffusers
ONNX
GGUF
conversational
Model card Files Files and versions
xet
Community

Instructions to use agkavin/Avatar-Speech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use agkavin/Avatar-Speech with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("agkavin/Avatar-Speech", dtype=torch.bfloat16, device_map="cuda")
    
    prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
    image = pipe(prompt).images[0]
  • llama-cpp-python

    How to use agkavin/Avatar-Speech with llama-cpp-python:

    # !pip install llama-cpp-python
    
    from llama_cpp import Llama
    
    llm = Llama.from_pretrained(
    	repo_id="agkavin/Avatar-Speech",
    	filename="backend/models/Llama-3.2-3B-Instruct-Q4_K_M.gguf",
    )
    
    llm.create_chat_completion(
    	messages = "No input example has been defined for this model task."
    )
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • llama.cpp

    How to use agkavin/Avatar-Speech with llama.cpp:

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

    How to use agkavin/Avatar-Speech with Ollama:

    ollama run hf.co/agkavin/Avatar-Speech:Q4_K_M
  • Unsloth Studio new

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

    How to use agkavin/Avatar-Speech with Docker Model Runner:

    docker model run hf.co/agkavin/Avatar-Speech:Q4_K_M
  • Lemonade

    How to use agkavin/Avatar-Speech with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull agkavin/Avatar-Speech:Q4_K_M
    Run and chat with the model
    lemonade run user.Avatar-Speech-Q4_K_M
    List all available models
    lemonade list
Avatar-Speech / frontend
956 kB
Ctrl+K
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  • 1 contributor
History: 3 commits
agkavin
Reorganize setup files and update documentation
21328a8 3 months ago
  • public
    Initial commit: speech_to_video project with models via LFS 3 months ago
  • src
    Reorganize setup files and update documentation 3 months ago
  • index.html
    376 Bytes
    Initial commit: speech_to_video project with models via LFS 3 months ago
  • package-lock.json
    66.8 kB
    merge 3 months ago
  • package.json
    570 Bytes
    merge 3 months ago
  • tsconfig.json
    562 Bytes
    Initial commit: speech_to_video project with models via LFS 3 months ago
  • tsconfig.node.json
    233 Bytes
    Initial commit: speech_to_video project with models via LFS 3 months ago
  • vite.config.ts
    380 Bytes
    Initial commit: speech_to_video project with models via LFS 3 months ago