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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 260 Bytes
8d54c4c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | {
"input_dim": 272,
"code_dim": 512,
"nb_code": 512,
"num_groups": 64,
"down_t": 2,
"stride_t": 2,
"width": 1024,
"depth": 3,
"dilation_growth_rate": 3,
"kernel_size": 3,
"activation": "relu",
"use_mgvq": true,
"absolute_root": true
} |