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:
- e3f99476f2e3dbf53e1a93a2eca3349d6d3d53ec8aa3e98f16e6a23ce5deb5a6
- Size of remote file:
- 595 MB
- SHA256:
- 93f55cd61e22710120eb4d7320661ba61de70d816b7e51e1b19502cabbea670a
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