Instructions to use CLMBR/old-existential-there-quantifier-lstm-0 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-0 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/old-existential-there-quantifier-lstm-0", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f27cdfdfc66635a98b3ebd5dff07b74cd50bdbbcc44e0ec6cac40f4ff10dd793
- Size of remote file:
- 4.28 kB
- SHA256:
- a5bc071f05c78e38eebaed0e58ea167b7befb7404c7d4e7540f3485c79ef4014
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.