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-2060640/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-2060640/pytorch_model.bin
- Command line
-
hf download hf://CLMBR/existential-there-quantifier-lstm-2/checkpoint-2060640/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/CLMBR/existential-there-quantifier-lstm-2/resolve/main/checkpoint-2060640/pytorch_model.bin
272 MB
- Xet hash:
- 12c687409cd218517662f7de19e9a9913b165ca0fa5e8b8614b14915405da754
- Size of remote file:
- 272 MB
- SHA256:
- 608c7ab85a513700bafdac6fe1cf25a7610be7196d43b5b95d639c1aa5173662
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