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:
- dfabe95a19f62e6686f5c2c9ed8c88fd3031237eac76828eceae3b2f8fbe854c
- Size of remote file:
- 272 MB
- SHA256:
- 9d094f59ee050561f60c33b4054827163a77cb5a97d59fc1bda474148e8a9206
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.