Instructions to use CLMBR/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/existential-there-quantifier-lstm-3 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/existential-there-quantifier-lstm-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-763200/training_args.bin from CLMBR/existential-there-quantifier-lstm-3: direct link, hf CLI and curl.
- Browser
- Download file 4.28 kB
-
https://huggingface.co/CLMBR/existential-there-quantifier-lstm-3/resolve/main/checkpoint-763200/training_args.bin
- Command line
-
hf download hf://CLMBR/existential-there-quantifier-lstm-3/checkpoint-763200/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CLMBR/existential-there-quantifier-lstm-3/resolve/main/checkpoint-763200/training_args.bin
4.28 kB
- Xet hash:
- 4ad7c2d2fe19e8d16d2f31030954bbaaf1fa3b07c46fcfa3f38c3a07e9615fe1
- Size of remote file:
- 4.28 kB
- SHA256:
- 7bedd85b2577dd35e80feaedbae877f1365db387cb34a0e9139af739ef184b57
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