Instructions to use CLMBR/full-lstm-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/full-lstm-2 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/full-lstm-2", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af1d7fe74e16703db15b8d9c29c5c517c3845a3e6eb3c13fcdcf3a1409fbee42
- Size of remote file:
- 272 MB
- SHA256:
- 9f6ba958dd277c689cfac9a3cbf46b70903a4e2ab88e1015e3fff873fd2a4eaa
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.