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:
# 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 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/fa837126e722bc362ab42dfa4957f51ff682fea3/pytorch_model.bin
- Command line
-
hf download hf://CLMBR/existential-there-quantifier-lstm-2@fa837126e722bc362ab42dfa4957f51ff682fea3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/CLMBR/existential-there-quantifier-lstm-2/resolve/fa837126e722bc362ab42dfa4957f51ff682fea3/pytorch_model.bin
272 MB
- Xet hash:
- 07297d0b86761963531274fc77926cccc6d30cca5046c61cb1871197dcc635c0
- Size of remote file:
- 272 MB
- SHA256:
- 235156b57d74fa10117d8831297804306814fa248d13fb2c056cf738b9bb4874
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