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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d3f3545d29613abf70e3d8f1c647da70668b2b5d773156697be44a4aa8dd934
- Size of remote file:
- 272 MB
- SHA256:
- 7198d9f46b36fe5c87149802f1978f978255e60ef5c288b5d56fb4f7fe564709
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.