Instructions to use andaqu/roBERTa-pers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use andaqu/roBERTa-pers with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, RobertaForMultiLabelSequenceClassification tokenizer = AutoTokenizer.from_pretrained("andaqu/roBERTa-pers") model = RobertaForMultiLabelSequenceClassification.from_pretrained("andaqu/roBERTa-pers", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from andaqu/roBERTa-pers: direct link, hf CLI and curl.
- Browser
- Download file 997 MB
-
https://huggingface.co/andaqu/roBERTa-pers/resolve/main/optimizer.pt
- Command line
-
hf download hf://andaqu/roBERTa-pers/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/andaqu/roBERTa-pers/resolve/main/optimizer.pt
997 MB
- Xet hash:
- 48c6ab26075131e7da2c310586cccb9e7565bd3aae5d2dd63fac64252f2bf7ea
- Size of remote file:
- 997 MB
- SHA256:
- 8ee14854303e979ce64534d92672df5cb7ebaea15924d4ae4e5ab896f3f12cf3
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