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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 28ad6076179be704953a1f2bea7580f81ff0330a56130411ca42ea1537149c40
- Size of remote file:
- 14.5 kB
- SHA256:
- 8f111e5db1c5f22768fafdf2fe55ad3f02fc16fa26026d5bbe9ffb65d08cd8a1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.