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:
- 43f386dc93efab3d7a5b764471cc6cbcdcd0b6afcf27a82f077f88fd04d7b9bb
- Size of remote file:
- 268 MB
- SHA256:
- b39441e0253c2b78c14dd2e937f6522e5307ec44d75ff6ce1e3ba1e30ada7221
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