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:
- 11c3d3388c24c478752ca574d6d64845741f9abf6d49cda2139a85355a0a1dbf
- Size of remote file:
- 272 MB
- SHA256:
- 11485656b96267359ce79963c2d22f7d18074364eb3763bafb252b013f89a6bb
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