Instructions to use Ayara31/shape_sorter0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use Ayara31/shape_sorter0 with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("<base-model-id>") model.load_adapter("Ayara31/shape_sorter0", set_active=True) - Notebooks
- Google Colab
- Kaggle
Download policy_postprocessor.json from Ayara31/shape_sorter0: direct link, hf CLI and curl.
- Browser
- Download file 660 Bytes
-
https://huggingface.co/Ayara31/shape_sorter0/resolve/refs%2Fpr%2F3/policy_postprocessor.json
- Command line
-
hf download hf://Ayara31/shape_sorter0@refs/pr/3/policy_postprocessor.json
-
curl -L -o policy_postprocessor.json https://huggingface.co/Ayara31/shape_sorter0/resolve/refs%2Fpr%2F3/policy_postprocessor.json
660 Bytes
| { | |
| "name": "policy_postprocessor", | |
| "steps": [ | |
| { | |
| "registry_name": "unnormalizer_processor", | |
| "config": { | |
| "eps": 1e-08, | |
| "features": { | |
| "action": { | |
| "type": "ACTION", | |
| "shape": [ | |
| 6 | |
| ] | |
| } | |
| }, | |
| "norm_map": { | |
| "VISUAL": "MEAN_STD", | |
| "STATE": "MEAN_STD", | |
| "ACTION": "MEAN_STD" | |
| } | |
| }, | |
| "state_file": "policy_postprocessor_step_0_unnormalizer_processor.safetensors" | |
| }, | |
| { | |
| "registry_name": "device_processor", | |
| "config": { | |
| "device": "cpu", | |
| "float_dtype": null | |
| } | |
| } | |
| ] | |
| } |