Instructions to use CLMBR/superlative-quantifier-lstm-0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/superlative-quantifier-lstm-0 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/superlative-quantifier-lstm-0", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4d09db0306e7ac0d004592683c9a0c13bf76fc11a64f5ba78782cd4b7518530b
- Size of remote file:
- 272 MB
- SHA256:
- c283bc98bb3c74e30afca76440d7d60b3a17afa1eab1fd29ac35f5c2a7f3247b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.