Instructions to use Cournane/roberta-base-reduced-Upper_pattern with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cournane/roberta-base-reduced-Upper_pattern with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cournane/roberta-base-reduced-Upper_pattern")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cournane/roberta-base-reduced-Upper_pattern") model = AutoModelForSequenceClassification.from_pretrained("Cournane/roberta-base-reduced-Upper_pattern") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 03a5a8a22e2312d4398c57489757be26b17b7a0e236946577db6ad9ff8f7e402
- Size of remote file:
- 499 MB
- SHA256:
- 88f4b43f669a380eb9a94dc577b16ec35008d54fd2518ff3ac158b173aff532e
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