Instructions to use CLMBR/old-existential-there-quantifier-lstm-1 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-1 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/old-existential-there-quantifier-lstm-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from CLMBR/old-existential-there-quantifier-lstm-1: direct link, hf CLI and curl.
- Browser
- Download file 4.28 kB
-
https://huggingface.co/CLMBR/old-existential-there-quantifier-lstm-1/resolve/3a0e39f8fe313cfb92fdc9d84d9ae292fe2c8e6e/training_args.bin
- Command line
-
hf download hf://CLMBR/old-existential-there-quantifier-lstm-1@3a0e39f8fe313cfb92fdc9d84d9ae292fe2c8e6e/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CLMBR/old-existential-there-quantifier-lstm-1/resolve/3a0e39f8fe313cfb92fdc9d84d9ae292fe2c8e6e/training_args.bin
4.28 kB
- Xet hash:
- 9878e432f6f3725af56567a396c8e33709741ac5939f9e3926f3ef0bd5178c31
- Size of remote file:
- 4.28 kB
- SHA256:
- 3d4f502a9fb9a2826167c0bb894e534f968b62a7afc6c49c75121e8e1c96e354
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