Robotics
Transformers
ONNX
Safetensors
PyTorch
mvae
feature-extraction
prosoro
multimodal
custom_code
Instructions to use prosoro/prosoro-mvae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prosoro/prosoro-mvae with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("prosoro/prosoro-mvae", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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modified: config.json
han-xudongmodified: cylinder/config.json modified: dome/config.json modified: neck/config.json modified: octagonal_prism/config.json modified: origami/config.json modified: quadrangular_prism/config.json8556d84
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modified: cylinder/model.safetensors
han-xudongmodified: dome/model.safetensors modified: neck/model.safetensors modified: octagonal_prism/model.safetensors modified: origami/model.safetensors modified: quadrangular_prism/model.safetensors7a1d06f
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new file: __init__.py
han-xudongnew file: config.json new file: cylinder/config.json new file: cylinder/model.onnx new file: cylinder/model.safetensors new file: dome/config.json new file: dome/model.onnx new file: dome/model.safetensors new file: modeling.py new file: neck/config.json new file: neck/model.onnx new file: neck/model.safetensors new file: octagonal_prism/config.json new file: octagonal_prism/model.onnx new file: octagonal_prism/model.safetensors new file: origami/config.json new file: origami/model.onnx new file: origami/model.safetensors new file: quadrangular_prism/config.json new file: quadrangular_prism/model.onnx new file: quadrangular_prism/model.safetensors6d097ab