Instructions to use Svetlana0303/Regression_longformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Svetlana0303/Regression_longformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Svetlana0303/Regression_longformer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Svetlana0303/Regression_longformer") model = AutoModelForSequenceClassification.from_pretrained("Svetlana0303/Regression_longformer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9646f3a57e195a2e45f6b0c85bdbedd75380d160ea9af0ad733dcaf7306a3389
- Size of remote file:
- 3.52 kB
- SHA256:
- 2d422dabdf2168baaef5e66c3aceeefa36d012894fafd1ba2d6a54b93e2b4156
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