Instructions to use CLMBR/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/existential-there-quantifier-lstm-2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/existential-there-quantifier-lstm-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-2136960/training_args.bin from CLMBR/existential-there-quantifier-lstm-2: direct link, hf CLI and curl.
- Browser
- Download file 4.28 kB
-
https://huggingface.co/CLMBR/existential-there-quantifier-lstm-2/resolve/main/checkpoint-2136960/training_args.bin
- Command line
-
hf download hf://CLMBR/existential-there-quantifier-lstm-2/checkpoint-2136960/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CLMBR/existential-there-quantifier-lstm-2/resolve/main/checkpoint-2136960/training_args.bin
4.28 kB
- Xet hash:
- 0966ae7928250be21e9a7197a78a13cc9907892e13aae699f96c7dd53dce6558
- Size of remote file:
- 4.28 kB
- SHA256:
- f731a04de7f8ce8f403259277267ff1b707eb3e5b7b94d817ccb1f0255a21a03
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