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] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use agkavin/Avatar-Speech 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 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 serve -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
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
- Atomic Chat
| # Speech-X Setup Guide | |
| Step-by-step install for the `avatar` conda environment. Adapted from the MuseTalk official docs for Python 3.12. | |
| Or run the automated script from the repo root: | |
| ```bash | |
| bash setup/setup.sh # Linux / macOS | |
| .\setup\setup.ps1 # Windows (PowerShell) | |
| ``` | |
| ## Stage 1: Create Environment | |
| ```bash | |
| conda create -n avatar python=3.12 | |
| conda activate avatar | |
| ``` | |
| ## Stage 2: Install PyTorch | |
| # Python 3.12 requires PyTorch 2.5+ (2.0.1 doesn't support 3.12) | |
| ```bash | |
| pip install torch==2.5.1 torchvision==0.20.1 torchaudio==2.5.1 --index-url https://download.pytorch.org/whl/cu124 | |
| ``` | |
| ## Stage 3: Install MMLab Packages | |
| # These are critical for MuseTalk - install one by one | |
| ```bash | |
| pip install --no-cache-dir -U openmim | |
| mim install mmengine | |
| mim install mmcv==2.2.0 | |
| # If above fails, try: pip install mmcv-lite==2.2.0 | |
| mim install mmdet==3.3.0 | |
| # Note: mmpose not required — not present in the reference env | |
| ``` | |
| ## Stage 4: Install Musetalk Dependencies | |
| # These are from musetalk's official requirements.txt | |
| ```bash | |
| pip install diffusers==0.30.2 | |
| pip install accelerate==0.28.0 | |
| pip install numpy==2.4.2 | |
| pip install opencv-python==4.13.0.92 | |
| pip install soundfile==0.12.1 | |
| pip install transformers==4.39.2 | |
| pip install huggingface-hub==0.36.2 | |
| pip install librosa==0.10.2 | |
| pip install einops==0.8.1 | |
| pip install gdown | |
| pip install requests | |
| pip install imageio==2.34.0 | |
| pip install imageio-ffmpeg | |
| pip install omegaconf==2.3.0 | |
| pip install ffmpeg-python | |
| pip install moviepy | |
| ``` | |
| ## Stage 5: Install Additional Dependencies | |
| # For this speech-to-video project | |
| ```bash | |
| pip install fastapi>=0.115.0 | |
| pip install uvicorn[standard]>=0.30.0 | |
| pip install pydantic>=2.10.0 | |
| pip install python-dotenv>=1.0.1 | |
| pip install livekit>=0.10.0 | |
| pip install livekit-agents>=0.8.0 | |
| pip install kokoro-onnx>=0.5.0 | |
| pip install scipy>=1.13.0 | |
| pip install faster-whisper>=1.0.0 | |
| pip install sse-starlette>=2.0.0 | |
| pip install onnxruntime>=1.24.0 | |
| pip install sounddevice>=0.5.0 | |
| pip install tqdm>=4.65.0 | |
| pip install pyyaml>=6.0.0 | |
| pip install aiohttp>=3.9.0 | |
| pip install httpx>=0.27.0 | |
| pip install safetensors>=0.4.0 | |
| pip install pillow>=10.0.0 | |
| ``` | |
| ## Quick Test | |
| ```bash | |
| # Test MuseTalk imports | |
| python -c " | |
| import sys | |
| sys.path.insert(0, 'backend') | |
| from musetalk.processor import * | |
| print('MuseTalk OK') | |
| " | |
| # Test TTS import | |
| python -c " | |
| import sys | |
| sys.path.insert(0, 'backend') | |
| from tts.kokoro_tts import KokoroTTS | |
| print('KokoroTTS OK') | |
| " | |
| ``` | |
| ## Avatar Creation | |
| Run once per avatar before starting the server. Script reads from `backend/config.py` | |
| for model paths and writes assets to `backend/avatars/<name>/`. | |
| **Single portrait image:** | |
| ```bash | |
| conda activate avatar | |
| python setup/avatar_creation.py --image frontend/public/Sophy.png --name sophy | |
| ``` | |
| **Talking-head video:** | |
| ```bash | |
| python setup/avatar_creation.py --video /path/to/talking_head.mp4 --name harry_1 | |
| ``` | |
| **Batch (multiple avatars at once):** | |
| ```bash | |
| # Edit setup/avatars_config.yml first, then: | |
| python setup/avatar_creation.py --config setup/avatars_config.yml | |
| ``` | |
| Options: | |
| | Flag | Default | Description | | |
| |------|---------|-------------| | |
| | `--name` | required | Avatar folder name | | |
| | `--frames` | `50` | Frame count for `--image` mode | | |
| | `--bbox-shift` | `5` | Vertical bbox nudge (tune if face crop is off) | | |
| | `--device` | `cuda` | `cuda` or `cpu` | | |
| | `--overwrite` | off | Skip re-create prompt | | |