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:
- e7ae4a06741c81c24a13273040817946e80b85e8b36a4fa0e5dd9bbf66baf870
- Size of remote file:
- 14.5 kB
- SHA256:
- 0d172dbd6a7046b44891108fe5c362da46ba177412b636c840a741eae941e781
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.