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:
- 27720e3700cef0d29809fab3b16af00f518c02714db854bb85fdf58f70445e2a
- Size of remote file:
- 272 MB
- SHA256:
- 4f4992a4ec82120cc02e337e85a21ff0f116ca955e5f7cc389cdfa4da74d98e8
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