Instructions to use CLMBR/old-existential-there-quantifier-lstm-3 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-3 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/old-existential-there-quantifier-lstm-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8f5028c94e21529010c7373afe672c13d1ed7c691dd8438f9e3603789ef8a506
- Size of remote file:
- 544 MB
- SHA256:
- c497275ea3de3602f6d9217b23667f26cf8e89f061e728d6d2e7525b7d524def
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.