Instructions to use binwang/roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use binwang/roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="binwang/roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("binwang/roberta-base") model = AutoModelForMaskedLM.from_pretrained("binwang/roberta-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d84ae86fbe04ad8d82c113192ec05cf17201cf9a7cbd0aa09a6b1739672c491c
- Size of remote file:
- 499 MB
- SHA256:
- 7647e7df15dfddb7d5c07fcbed7a21e3881ccfea085791cf09917aa05947bba3
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