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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c7585c1a660a2b8a045a683d7a9c873d317aaaa160169ee0845b47121dd2fe73
- Size of remote file:
- 272 MB
- SHA256:
- 40d2ea4c8439e7a18dc2a25c871b83ed6f6136e5cd3d1cc90fb4eba7bdbb0420
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