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:
- 4d05a285fef008e937fb4c153b3fe32384f4f3f5eb0980f30fea3991ed840d3e
- Size of remote file:
- 272 MB
- SHA256:
- 0196252e01209aa1a27e790d6a368b28b4c4d218441b26a0ca84fead9075c2db
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.