Instructions to use CLMBR/old-existential-there-quantifier-lstm-2 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-2 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/old-existential-there-quantifier-lstm-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 976a874c91fa64a12d2dbfee2e6d9d724daa0bc1a22cf51c231f77e504828bb8
- Size of remote file:
- 272 MB
- SHA256:
- be0c58582d8d8b647c65268179f546ce42ffeb38f2ed31ad739f0684fa10f624
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.