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:
- f0101e0ec9a5674630e5478051ef599224f89b6621ed7f7427d379fb2d6d71ee
- Size of remote file:
- 272 MB
- SHA256:
- 2162fb88de9747613410c25e186c0ccfed5032538f8de07118522d23c3b01639
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.