Instructions to use CLMBR/old-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/old-existential-there-quantifier-lstm-4 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/old-existential-there-quantifier-lstm-4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-1908000/training_args.bin from CLMBR/old-existential-there-quantifier-lstm-4: direct link, hf CLI and curl.
- Browser
- Download file 4.28 kB
-
https://huggingface.co/CLMBR/old-existential-there-quantifier-lstm-4/resolve/main/checkpoint-1908000/training_args.bin
- Command line
-
hf download hf://CLMBR/old-existential-there-quantifier-lstm-4/checkpoint-1908000/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CLMBR/old-existential-there-quantifier-lstm-4/resolve/main/checkpoint-1908000/training_args.bin
4.28 kB
- Xet hash:
- 074c5938e1f684cbd536d91109b08159bbe70e04acb807b447c085cb919bac62
- Size of remote file:
- 4.28 kB
- SHA256:
- e4b1fced26c54312afdbe6e199c93f8ca5ab37c06a14bc751fbf4843d9e61ce0
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