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:
- d7ca1489773cfc678f256db9018b4d55866ce3d4d6242faf0236995e04515441
- Size of remote file:
- 272 MB
- SHA256:
- 01a3f0d1a4505d520b8c6de3b7e4a665ae1deb5ae674c3bba0c57af4f6cdc787
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.