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 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/training_args.bin
- Command line
-
hf download hf://CLMBR/existential-there-quantifier-lstm-4/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CLMBR/existential-there-quantifier-lstm-4/resolve/main/training_args.bin
4.28 kB
- Xet hash:
- 32669393764ab2e40fe1651b5ae27bcaee9124195829e1e6a2aa75bed37ca3d3
- Size of remote file:
- 4.28 kB
- SHA256:
- d40c695c017b94eeb80ca81ba1bbe6b71b93360c873de202f05b839f3ba0cc21
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