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:
- 6fe782362e8d6947987e7f031992d774ed20a54fc798ac712cee9506aa4646b2
- Size of remote file:
- 272 MB
- SHA256:
- c43dda86a38c93286f531fdc09a5aa1d62a753402b9795ad2fd6e934fade90e1
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