Instructions to use CLMBR/old-pp-mod-subj-lstm-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/old-pp-mod-subj-lstm-3 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/old-pp-mod-subj-lstm-3", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 90069a0117c9554db36138ff1bc4e73b5395c09a1019dd3901798468e70f8e81
- Size of remote file:
- 272 MB
- SHA256:
- 57d98eb11c70e1409ba9c1abcbfd6a80d45c8fd9f14d7d64001a06bcfd5dec04
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.