Instructions to use CLMBR/old-full-lstm-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/old-full-lstm-4 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/old-full-lstm-4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 79e3948aea8870f77b13ed35af06f0450bf1ba0cd1f88f3aaa8c41287079cda5
- Size of remote file:
- 272 MB
- SHA256:
- b6faacb9dba274de821ba2fde729d4dee2010ec8915e61c54095add70053abe3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.