Instructions to use CLMBR/superlative-quantifier-lstm-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/superlative-quantifier-lstm-3 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/superlative-quantifier-lstm-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-2594880/training_args.bin from CLMBR/superlative-quantifier-lstm-3: direct link, hf CLI and curl.
- Browser
- Download file 4.28 kB
-
https://huggingface.co/CLMBR/superlative-quantifier-lstm-3/resolve/main/checkpoint-2594880/training_args.bin
- Command line
-
hf download hf://CLMBR/superlative-quantifier-lstm-3/checkpoint-2594880/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CLMBR/superlative-quantifier-lstm-3/resolve/main/checkpoint-2594880/training_args.bin
4.28 kB
- Xet hash:
- 13d79ba80c8924bb232c744a2c988d3783c240d9943b51f528c9b5a804077619
- Size of remote file:
- 4.28 kB
- SHA256:
- 736d1a6d1424d25dfe8676be04082e62a818866338b4e99fd8caa1263ca28b74
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