Instructions to use CLMBR/existential-there-quantifier-lstm-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/existential-there-quantifier-lstm-2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/existential-there-quantifier-lstm-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-2747520/optimizer.pt from CLMBR/existential-there-quantifier-lstm-2: direct link, hf CLI and curl.
- Browser
- Download file 544 MB
-
https://huggingface.co/CLMBR/existential-there-quantifier-lstm-2/resolve/main/checkpoint-2747520/optimizer.pt
- Command line
-
hf download hf://CLMBR/existential-there-quantifier-lstm-2/checkpoint-2747520/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/CLMBR/existential-there-quantifier-lstm-2/resolve/main/checkpoint-2747520/optimizer.pt
544 MB
- Xet hash:
- 19bf11aa116e4fe78ad47f2f42c734c69714150aaabff6a1460388fe806fd5b7
- Size of remote file:
- 544 MB
- SHA256:
- 4029007dbe510c811a416eb210a301d31cac8c15b00ad1c44e1ed1885d56d5a5
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