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-686880/optimizer.pt from CLMBR/existential-there-quantifier-lstm-2: direct link, hf CLI and curl.
- Browser
- Download file 544 MB
-
https://huggingface.co/CLMBR/existential-there-quantifier-lstm-2/resolve/main/checkpoint-686880/optimizer.pt
- Command line
-
hf download hf://CLMBR/existential-there-quantifier-lstm-2/checkpoint-686880/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/CLMBR/existential-there-quantifier-lstm-2/resolve/main/checkpoint-686880/optimizer.pt
544 MB
- Xet hash:
- cdf7cfcf80064daa9e6c4cb295acc844d23f860f44914ec91bca08365832ddf0
- Size of remote file:
- 544 MB
- SHA256:
- 6aeb890fa26227bb7480f3581d0ff66af5249103547cc109c63e35ba7240e37f
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