Instructions to use Cournane/roberta-base-reduced-Lower_pattern with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cournane/roberta-base-reduced-Lower_pattern with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cournane/roberta-base-reduced-Lower_pattern")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cournane/roberta-base-reduced-Lower_pattern") model = AutoModelForSequenceClassification.from_pretrained("Cournane/roberta-base-reduced-Lower_pattern") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c2f6df89478077534ff5b55742ef9f6910f89ee30edae01c158f81b27c0dd0e9
- Size of remote file:
- 499 MB
- SHA256:
- d363b3975210e484b18ce2d5093d198e872f10796678283c5317f2e219bcdd79
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