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:
- 39ae95c09c8be3211765a141435ea31a650630092048c08292feacc32c0c9f4c
- Size of remote file:
- 4.28 kB
- SHA256:
- f27bab35645a6520c63e720694519bab5d78ca8f7037baad8fbb8435595ff420
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.