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@@ -306,26 +306,6 @@ reproduces SOTA results for Diffusion Policy on the PushT task.
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If you would like to contribute to 🤗 LeRobot, please check out our [contribution guide](https://github.com/huggingface/lerobot/blob/main/CONTRIBUTING.md).
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<!-- ### Add a new dataset
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To add a dataset to the hub, you need to login using a write-access token, which can be generated from the [Hugging Face settings](https://huggingface.co/settings/tokens):
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```bash
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huggingface-cli login --token ${HUGGINGFACE_TOKEN} --add-to-git-credential
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```
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Then point to your raw dataset folder (e.g. `data/aloha_static_pingpong_test_raw`), and push your dataset to the hub with:
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```bash
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python lerobot/scripts/push_dataset_to_hub.py \
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--raw-dir data/aloha_static_pingpong_test_raw \
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--out-dir data \
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--repo-id lerobot/aloha_static_pingpong_test \
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--raw-format aloha_hdf5
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```
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See `python lerobot/scripts/push_dataset_to_hub.py --help` for more instructions.
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If your dataset format is not supported, implement your own in `lerobot/datasets/push_dataset_to_hub/${raw_format}_format.py` by copying examples like [pusht_zarr](https://github.com/huggingface/lerobot/blob/main/lerobot/datasets/push_dataset_to_hub/pusht_zarr_format.py), [umi_zarr](https://github.com/huggingface/lerobot/blob/main/lerobot/datasets/push_dataset_to_hub/umi_zarr_format.py), [aloha_hdf5](https://github.com/huggingface/lerobot/blob/main/lerobot/datasets/push_dataset_to_hub/aloha_hdf5_format.py), or [xarm_pkl](https://github.com/huggingface/lerobot/blob/main/lerobot/datasets/push_dataset_to_hub/xarm_pkl_format.py). -->
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### Add a pretrained policy
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Once you have trained a policy you may upload it to the Hugging Face hub using a hub id that looks like `${hf_user}/${repo_name}` (e.g. [lerobot/diffusion_pusht](https://huggingface.co/lerobot/diffusion_pusht)).
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