Instructions to use CLMBR/old-rel-cl-lstm-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/old-rel-cl-lstm-4 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/old-rel-cl-lstm-4", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c9189cd1e0f583952ec7eb0029c9cb3ed5a76924725afa39f4207a6341cd457
- Size of remote file:
- 272 MB
- SHA256:
- 08948914641a68a6f3c0108173b8c42a3a6d119ae5e9e03baed028bd84fc95aa
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.