Instructions to use CLMBR/old-existential-there-quantifier-lstm-4 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-4 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/old-existential-there-quantifier-lstm-4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2c7ca9d5ed5e8cce6e9ee47831f448e172aeadb425334cfe8e889cae1aefa3f7
- Size of remote file:
- 4.28 kB
- SHA256:
- 45dbf79268ac07ae178ce630e5efc8faece0d4181d870b06ab45cf3e676fb267
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.