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:
- 81cedb68a2a05e8365e797d7ac2a7ae3958cf5f9b2bcc9edb459a99e29f5cb88
- Size of remote file:
- 544 MB
- SHA256:
- 832f51713104107ecc246f5daf0f5ceb8c776190bdc83d01cb6fa64a32faa428
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.