Instructions to use Drigoro/deberta_normal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Drigoro/deberta_normal with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Drigoro/deberta_normal")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Drigoro/deberta_normal") model = AutoModelForSequenceClassification.from_pretrained("Drigoro/deberta_normal") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5733364871ef1a76115e882965247785b246b3ac8e71d70b8d1729fe1eac6959
- Size of remote file:
- 557 MB
- SHA256:
- 607c51afbc8085e8ac3d69a400d7e792e0fbd5d921081ae8df5aa4c2dd05ad9f
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