Instructions to use CLMBR/superlative-quantifier-lstm-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/superlative-quantifier-lstm-2 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/superlative-quantifier-lstm-2", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 37ed950982469dd41b2f54d6d2eb503ccfce673687dc6e2648388254a9b19395
- Size of remote file:
- 272 MB
- SHA256:
- 221bd0117f43b7af6290a155c50774a1b914fe15ee658cb367b02f3c1737078d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.