Instructions to use copenlu/scientific-exaggeration-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use copenlu/scientific-exaggeration-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="copenlu/scientific-exaggeration-detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("copenlu/scientific-exaggeration-detection") model = AutoModelForSequenceClassification.from_pretrained("copenlu/scientific-exaggeration-detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f0ad81d2ea5a11c10672dedccb92a53bc201012e3ffd124d1008daea147b9bf
- Size of remote file:
- 499 MB
- SHA256:
- c1472e0d7b47d8a5ece381d1b9ba7ba1c940becbdf5168918d5e3cdc3fe21d88
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