Instructions to use CLMBR/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/existential-there-quantifier-lstm-4 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/existential-there-quantifier-lstm-4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-1679040/optimizer.pt from CLMBR/existential-there-quantifier-lstm-4: direct link, hf CLI and curl.
- Browser
- Download file 544 MB
-
https://huggingface.co/CLMBR/existential-there-quantifier-lstm-4/resolve/main/checkpoint-1679040/optimizer.pt
- Command line
-
hf download hf://CLMBR/existential-there-quantifier-lstm-4/checkpoint-1679040/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/CLMBR/existential-there-quantifier-lstm-4/resolve/main/checkpoint-1679040/optimizer.pt
544 MB
- Xet hash:
- 5cd0f6c7f435323662bca8bf146a963a48b2d8998db3b334ccf6284e8a9575a6
- Size of remote file:
- 544 MB
- SHA256:
- 5ee1da72244a7ada16972083d0c4372e6504d9ffbbcadfc691afddeced8d37d4
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