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-76320/optimizer.pt from CLMBR/existential-there-quantifier-lstm-4: direct link, hf CLI and curl.
- Browser
- Download file 544 MB
-
https://huggingface.co/CLMBR/existential-there-quantifier-lstm-4/resolve/main/checkpoint-76320/optimizer.pt
- Command line
-
hf download hf://CLMBR/existential-there-quantifier-lstm-4/checkpoint-76320/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/CLMBR/existential-there-quantifier-lstm-4/resolve/main/checkpoint-76320/optimizer.pt
544 MB
- Xet hash:
- f2d17856982cf3c60d2307ee120b73f9330f3e71d96bf4b4fde6721a7bd4aca0
- Size of remote file:
- 544 MB
- SHA256:
- b3af9e1367338a465b77b870221b764c6d861a16ee5ea1bd6f51782795a88abc
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