Robotics
Transformers
ONNX
Safetensors
PyTorch
mvae
feature-extraction
prosoro
multimodal
custom_code
Instructions to use han-xudong/prosoro-mvae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use han-xudong/prosoro-mvae with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("han-xudong/prosoro-mvae", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 74accb581a80c74087c2ba53827602d3b171aac4996d62a43ab83f4dc3cb5dd7
- Size of remote file:
- 39.8 MB
- SHA256:
- 8514ef4d6db1be2b52af20e9e182c2b55756396c7d095dc0c774466a7454ca9a
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