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-457920/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-457920/training_args.bin
- Command line
-
hf download hf://CLMBR/existential-there-quantifier-lstm-3/checkpoint-457920/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CLMBR/existential-there-quantifier-lstm-3/resolve/main/checkpoint-457920/training_args.bin
4.28 kB
- Xet hash:
- 4189e1de402329924a9aa4f8898df79ec30466455962c55c11bd6a39457b6dd2
- Size of remote file:
- 4.28 kB
- SHA256:
- 73e338a20916d0159cbaceb8fd3498a564f6a03e7ece6aa5a71fae38e3876d8a
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