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-610560/pytorch_model.bin from CLMBR/existential-there-quantifier-lstm-2: direct link, hf CLI and curl.
- Browser
- Download file 272 MB
-
https://huggingface.co/CLMBR/existential-there-quantifier-lstm-2/resolve/main/checkpoint-610560/pytorch_model.bin
- Command line
-
hf download hf://CLMBR/existential-there-quantifier-lstm-2/checkpoint-610560/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/CLMBR/existential-there-quantifier-lstm-2/resolve/main/checkpoint-610560/pytorch_model.bin
272 MB
- Xet hash:
- db8b668a1b4e8c2c58f0ea1959a775c3ad195b820f1832b682e64e76550ab64f
- Size of remote file:
- 272 MB
- SHA256:
- 2d0801cb5bcd6bd0b1e8a7a5d84d9e95a9f9b4b4962215ef7cfdd72d8b225eaf
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