Instructions to use Arthuerwang/roberta-base-tutorial with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Arthuerwang/roberta-base-tutorial with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Arthuerwang/roberta-base-tutorial")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Arthuerwang/roberta-base-tutorial") model = AutoModelForMaskedLM.from_pretrained("Arthuerwang/roberta-base-tutorial") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 22df5e1ee81e7b87ee12f739023e35d186e00862df1a1b9634649a3ef5b045ab
- Size of remote file:
- 499 MB
- SHA256:
- 13f3c0666d13bba280c6295762c5585f61521b6a2e571c05699e660823cf4866
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