Instructions to use CLMBR/superlative-quantifier-lstm-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/superlative-quantifier-lstm-4 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/superlative-quantifier-lstm-4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-1297440/scheduler.pt from CLMBR/superlative-quantifier-lstm-4: direct link, hf CLI and curl.
- Browser
- Download file 627 Bytes
-
https://huggingface.co/CLMBR/superlative-quantifier-lstm-4/resolve/main/checkpoint-1297440/scheduler.pt
- Command line
-
hf download hf://CLMBR/superlative-quantifier-lstm-4/checkpoint-1297440/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/CLMBR/superlative-quantifier-lstm-4/resolve/main/checkpoint-1297440/scheduler.pt
627 Bytes
- Xet hash:
- 4ad8cc10ce5a01ed129d17b096921d16ce25eb857c657af37e7ee41d95f0a088
- Size of remote file:
- 627 Bytes
- SHA256:
- 9883db46ab3004d49db8a5ce5311c22f32829f1c5eb1198422547a592366d277
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