Instructions to use CLMBR/superlative-quantifier-lstm-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/superlative-quantifier-lstm-1 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/superlative-quantifier-lstm-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ef6ade061f87b0cf93f4765206c2b9588d62a74fc4015bf4eca04124502681f1
- Size of remote file:
- 627 Bytes
- SHA256:
- e48f496945983edbcd1b42d1641e7b2444a2d10dd65f2a8a5567b6787d43b954
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.