Instructions to use CLMBR/old-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/old-existential-there-quantifier-lstm-1 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/old-existential-there-quantifier-lstm-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 69bef351d7999c52c030a17d4d660895059019fb6575c1aa510781d1ce714b53
- Size of remote file:
- 544 MB
- SHA256:
- 8bc927b42c04b6ddac6779d0d51eb6141268469ba776c1ad74b538adf3059b25
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.