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:
- 459542a2206c1768e460b2260cef4658e150d5a26ce8cae5b801ed09058dbde8
- Size of remote file:
- 4.22 kB
- SHA256:
- 488757da45fb9df93dacfcfa5a475915620bf88ecdcceacdbae6946a94631920
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.