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-457920/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-457920/optimizer.pt
- Command line
-
hf download hf://CLMBR/existential-there-quantifier-lstm-2/checkpoint-457920/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/CLMBR/existential-there-quantifier-lstm-2/resolve/main/checkpoint-457920/optimizer.pt
544 MB
- Xet hash:
- 5480ee525f07c39be95e710dd3f8e92b32bbe731ea58b96fa2795bb815e6bf7f
- Size of remote file:
- 544 MB
- SHA256:
- 36717ddce72687367073d12a25a233da2a89a0f6eb750581a4709e76a0827817
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