Instructions to use CLMBR/existential-there-quantifier-lstm-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/existential-there-quantifier-lstm-1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/existential-there-quantifier-lstm-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-992160/optimizer.pt from CLMBR/existential-there-quantifier-lstm-1: direct link, hf CLI and curl.
- Browser
- Download file 544 MB
-
https://huggingface.co/CLMBR/existential-there-quantifier-lstm-1/resolve/main/checkpoint-992160/optimizer.pt
- Command line
-
hf download hf://CLMBR/existential-there-quantifier-lstm-1/checkpoint-992160/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/CLMBR/existential-there-quantifier-lstm-1/resolve/main/checkpoint-992160/optimizer.pt
544 MB
- Xet hash:
- b04532fe09b144a16037a73ca3a8702364bd2e7086b3848aa382e91eeacf4e65
- Size of remote file:
- 544 MB
- SHA256:
- d52b668301d92e6b7110a7c0934c636a715f3895fc1cbcd70a5efe7fa834a408
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