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-839520/rng_state.pth from CLMBR/existential-there-quantifier-lstm-4: direct link, hf CLI and curl.
- Browser
- Download file 14.6 kB
-
https://huggingface.co/CLMBR/existential-there-quantifier-lstm-4/resolve/main/checkpoint-839520/rng_state.pth
- Command line
-
hf download hf://CLMBR/existential-there-quantifier-lstm-4/checkpoint-839520/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/CLMBR/existential-there-quantifier-lstm-4/resolve/main/checkpoint-839520/rng_state.pth
14.6 kB
- Xet hash:
- 96b345edc82538d4ad60c4b830965e974d0be30c4b94b23e7e3124939da08e0f
- Size of remote file:
- 14.6 kB
- SHA256:
- 102126f2a25f9b959b3a856f648bd06849a8e10b9b3294d8c09ab31e6b4054b1
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