Instructions to use TJ-chen/RDT-1B-LIBERO-Long with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TJ-chen/RDT-1B-LIBERO-Long with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TJ-chen/RDT-1B-LIBERO-Long", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download scheduler.bin from TJ-chen/RDT-1B-LIBERO-Long: direct link, hf CLI and curl.
- Browser
- Download file 1 kB
-
https://huggingface.co/TJ-chen/RDT-1B-LIBERO-Long/resolve/main/scheduler.bin
- Command line
-
hf download hf://TJ-chen/RDT-1B-LIBERO-Long/scheduler.bin
-
curl -L -o scheduler.bin https://huggingface.co/TJ-chen/RDT-1B-LIBERO-Long/resolve/main/scheduler.bin
1 kB
- Xet hash:
- a6a23e4a8371f75b721b5e503ac35e92e5ab40f2cceeefae81d5ac664c4172e3
- Size of remote file:
- 1 kB
- SHA256:
- 7dc20233eac91546329cf291de0d1ab3b081d9ac406b1bee193bf31f05b8329f
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