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:
- 2540933192a02d7a1e0deb6451849712f8f33e5ebbc7421e9338c8f29f521488
- Size of remote file:
- 14.5 kB
- SHA256:
- f01f8b35c2be430e4eb91293df411cfcf390acace78b27f41d5a14d400873fd7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.