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 pytorch_model.bin from andaqu/roBERTa-pers: direct link, hf CLI and curl.
- Browser
- Download file 501 MB
-
https://huggingface.co/andaqu/roBERTa-pers/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://andaqu/roBERTa-pers/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/andaqu/roBERTa-pers/resolve/main/pytorch_model.bin
501 MB
- Xet hash:
- ef9ab622d755f87f30dfa1531fb5a9ec9fdd29805a67f87fa74d49fbf921259e
- Size of remote file:
- 501 MB
- SHA256:
- c10312e296bab4080fd74e3db025a58c7e8645d9602aa49846fcccae017ab3ac
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