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 training_args.bin from CLMBR/existential-there-quantifier-lstm-2: direct link, hf CLI and curl.
- Browser
- Download file 4.28 kB
-
https://huggingface.co/CLMBR/existential-there-quantifier-lstm-2/resolve/fa837126e722bc362ab42dfa4957f51ff682fea3/training_args.bin
- Command line
-
hf download hf://CLMBR/existential-there-quantifier-lstm-2@fa837126e722bc362ab42dfa4957f51ff682fea3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CLMBR/existential-there-quantifier-lstm-2/resolve/fa837126e722bc362ab42dfa4957f51ff682fea3/training_args.bin
4.28 kB
- Xet hash:
- aff44d027011ff7c6148b91bbf71023b6d1a66bd0f7d02b25980b8172a74fe6b
- Size of remote file:
- 4.28 kB
- SHA256:
- e5453914e34120862527c8e3e050482e71438835183b1ded1a21db10f50f9cbe
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