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:
- 043dd6b7edd1029ede163f572061e0ad305ad3804f63eb13d37762cb4ccae063
- Size of remote file:
- 272 MB
- SHA256:
- 074329727e87ba9863a5a882b60252c72b7dd4fd992dfd5d942a14e98f44189d
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