Instructions to use ZibinDong/ActionCodec-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZibinDong/ActionCodec-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ZibinDong/ActionCodec-Base", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ZibinDong/ActionCodec-Base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e4d4da054dd7544c852fc09b36f0609a58446a32cba2f0887b23c85086a0707a
- Size of remote file:
- 180 MB
- SHA256:
- 19c172a0417a8b1f22671bd8be5fa7327410f0afe23c8a64312fde4a3c2d297b
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