Instructions to use CLMBR/binding-case-lstm-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/binding-case-lstm-2 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/binding-case-lstm-2", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c37656047cfd62bd2fca853a57796f38541ed53ae2ed630b8ae8fc9b5b85faa3
- Size of remote file:
- 272 MB
- SHA256:
- 9b9e862454c553e60182ddb47821f7f3d3780893ad28aaac5df300edce3abbaa
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.