Instructions to use q3fer/distilbert-base-fallacy-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use q3fer/distilbert-base-fallacy-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="q3fer/distilbert-base-fallacy-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("q3fer/distilbert-base-fallacy-classification") model = AutoModelForSequenceClassification.from_pretrained("q3fer/distilbert-base-fallacy-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ac430723d1023815eec93655f5e50386206fbdde6915f9ef5855629b674d85f
- Size of remote file:
- 268 MB
- SHA256:
- 4157a11b18f429cabd361d304881c8c3fe1f34b498a4cedeb3bb45c9dfbbd340
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