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:
- 4cf82c90e79060d5cf11ca692233c5c9526e313d39d9640475dfb3786947a956
- Size of remote file:
- 4.28 kB
- SHA256:
- 8bf84805157e1e3746101af66a36af9ec0f514562c0437a1ed12a6db1a4f2697
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.