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:
- f9bbc69607904b945cdf4efb7e706a7c43311ee4e71a9faffe1779ea3e8bbf5e
- Size of remote file:
- 627 Bytes
- SHA256:
- cd1730889dc70ec9805ae87b6feb5bd1c27c2f98fd1dade88bdaae940f01c58d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.