Instructions to use CLMBR/old-existential-there-quantifier-lstm-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/old-existential-there-quantifier-lstm-3 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/old-existential-there-quantifier-lstm-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0be1a767e6f1812f2e442183fcc5c96eee15e80ae88d6fa830d3257f5da30642
- Size of remote file:
- 544 MB
- SHA256:
- 13e1c0bbc29c927f707c5d4ef744e05b12c039bb9b9decffc1b2d5874f20f96b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.