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:
- ea0ab846c74c730011c801f8ba1c17047a175ad16c9b3577e0612c359cc81401
- Size of remote file:
- 4.22 kB
- SHA256:
- df4c0f9403a6e6113ce329360dab1e12a82791fa5fa4dd166bcf7253d8c2367e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.