Instructions to use CLMBR/passive-lstm-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/passive-lstm-3 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/passive-lstm-3", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 543c9f59de2d9e790c0e131d1629e797bf67ad0b7b7e8bfbcc27cb36347a8b5b
- Size of remote file:
- 272 MB
- SHA256:
- f0e94292f0fa3f9f10b71b61942f2e4452cc10331c3e0feae2283b42c3bc7558
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