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:
- 2fa17dcd80e65e5d86ee6449c86588468273bd998f37e76893f0207a1d79e7e1
- Size of remote file:
- 272 MB
- SHA256:
- 7a172e6bffeb3b1a36124bae8c37902bf3488b0324dbf14f5417e9b87d2fd2d3
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