Instructions to use CLMBR/binding-reconstruction-lstm-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/binding-reconstruction-lstm-1 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/binding-reconstruction-lstm-1", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- be01534fca163e541577125d533a13315de252d6c6d40a086349f4db59243b5d
- Size of remote file:
- 4.28 kB
- SHA256:
- 8f9692daaeff41ce8b64bad50be264a259d6c76a981dd7100992b3ab6d401b85
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.