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:
# pip install -U transformers accelerate # 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 checkpoint-2823840/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/main/checkpoint-2823840/training_args.bin
- Command line
-
hf download hf://CLMBR/old-existential-there-quantifier-lstm-1/checkpoint-2823840/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CLMBR/old-existential-there-quantifier-lstm-1/resolve/main/checkpoint-2823840/training_args.bin
4.28 kB
- Xet hash:
- d40bde62d902f52d25a6a7c81ea7197e41a0c5c7c8d00b594758da89a6d85b4b
- Size of remote file:
- 4.28 kB
- SHA256:
- f8345986f406b481a4d58ec17d566788a8609aeff0d8514c469faf08fcb409fc
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