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:
- fce41953aac5aa7671c310123a16a640ff758813b249008fd3672274181c4f52
- Size of remote file:
- 272 MB
- SHA256:
- 55a2cc282e3c3ac053373d994b357a14e9741da07aa1d9ab73130ad13ac83e33
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