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-2136960/training_args.bin from CLMBR/existential-there-quantifier-lstm-4: direct link, hf CLI and curl.
- Browser
- Download file 4.28 kB
-
https://huggingface.co/CLMBR/existential-there-quantifier-lstm-4/resolve/main/checkpoint-2136960/training_args.bin
- Command line
-
hf download hf://CLMBR/existential-there-quantifier-lstm-4/checkpoint-2136960/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CLMBR/existential-there-quantifier-lstm-4/resolve/main/checkpoint-2136960/training_args.bin
4.28 kB
- Xet hash:
- f65ccbb9f48c022cd2096e6565f41c68ef73dc972cc1f718f891895cffc74eb4
- Size of remote file:
- 4.28 kB
- SHA256:
- f4f03346ab460a688bafa7b64ad50a49ef83e591d5869373f3b7c0165b21d2a6
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