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 checkpoint-457920/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/checkpoint-457920/training_args.bin
- Command line
-
hf download hf://CLMBR/existential-there-quantifier-lstm-4/checkpoint-457920/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CLMBR/existential-there-quantifier-lstm-4/resolve/main/checkpoint-457920/training_args.bin
4.28 kB
- Xet hash:
- 5ae8cf6475467d3085dea567e597c58c2321ed8fe182bb32b2f22ae375428c89
- Size of remote file:
- 4.28 kB
- SHA256:
- 5c6f44c6c01fa06758ee91d9a3e0f7e431408b339a2f2926dc07a8a3a3791e9a
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