Instructions to use CLMBR/old-existential-there-quantifier-lstm-2 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-2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/old-existential-there-quantifier-lstm-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from CLMBR/old-existential-there-quantifier-lstm-2: direct link, hf CLI and curl.
- Browser
- Download file 4.28 kB
-
https://huggingface.co/CLMBR/old-existential-there-quantifier-lstm-2/resolve/main/training_args.bin
- Command line
-
hf download hf://CLMBR/old-existential-there-quantifier-lstm-2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CLMBR/old-existential-there-quantifier-lstm-2/resolve/main/training_args.bin
4.28 kB
- Xet hash:
- 295deacb0933b41c707c3188da574c9b174c70722f900503f7c090d75d04b7c1
- Size of remote file:
- 4.28 kB
- SHA256:
- 6f7b6a246413a7a5a78f79baa11d62edd3e7e0dae1d87fe9d823f28ec41cbb72
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