Instructions to use CLMBR/existential-there-quantifier-lstm-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/existential-there-quantifier-lstm-1 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/existential-there-quantifier-lstm-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f6d5711594bb00b8c5be7c0802347ad8e6941db9fc5807f79d9ddb23d76149d9
- Size of remote file:
- 272 MB
- SHA256:
- 974986a088094cd151d33963a2145ccd7ee5dda1697662095fb2cf10b5d6e8ec
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.