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:
- 67b97adaf030addcc747c21a3121219a99e3e3e872b1f49016c4c2ffae5cd462
- Size of remote file:
- 14.5 kB
- SHA256:
- c3276bf1fcac073f3e734eb8c4f880343de6b9263f7c72bad174dbc942a59e5b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.