Other
Transformers
Safetensors
ldf_motion
feature-extraction
text-to-motion
motion-generation
diffusion-forcing
humanml3d
computer-animation
custom_code
Instructions to use AlayaLab/FloodDiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlayaLab/FloodDiffusion with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AlayaLab/FloodDiffusion", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add EMA smoothing support for joint positions
- Add smoothing_alpha parameter to model() API (default=1.0, no smoothing) - Implement EMA smoothing in StreamJointRecovery263 class - Support batch generation with independent smoothing per sample - Update README with usage examples and API documentation - Add .gitignore for cache and temporary files Usage: model(text, length=60, output_joints=True, smoothing_alpha=0.5)82d5f99