Feature Extraction
Transformers
PyTorch
English
motion
vqvae
motion-tokenization
motion-generation
human-motion
vector-quantization
Instructions to use khania/motion-mgvqvae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use khania/motion-mgvqvae with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="khania/motion-mgvqvae")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("khania/motion-mgvqvae", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13f3fb8acbd9f0edf50a54208f5cd7bd244a24bb24f5fd9dbb71ca95dafcbd0e
- Size of remote file:
- 293 MB
- SHA256:
- 748e60e09ec022ce08e5e336194bf9d3280076502979a6486dddd063c0f502d5
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