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:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("prosoro/prosoro-mvae", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "asRobotics/prosoro-mvae", | |
| "architectures": ["MVAE"], | |
| "model_type": "mvae", | |
| "prosoro_type": "quadrangular_prism", | |
| "x_dim_dict": [6, 6, 1740], | |
| "h1_dim_dict": [8, 8, 1024], | |
| "h2_dim_dict": [16, 16, 256], | |
| "z_dim": 32, | |
| "torch_dtype": "float32", | |
| "layer_norm": false, | |
| "use_activation": "relu", | |
| "auto_map": { | |
| "AutoConfig": "modeling.MVAEConfig", | |
| "AutoModel": "modeling.MVAE" | |
| } | |
| } |