Text Classification
Transformers
PyTorch
German
distilbert
fearspeech
classification
social science
communication
hatespeech
text-embeddings-inference
Instructions to use PatrickSchwabl/distilbert_fearspeech_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PatrickSchwabl/distilbert_fearspeech_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PatrickSchwabl/distilbert_fearspeech_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PatrickSchwabl/distilbert_fearspeech_classifier") model = AutoModelForSequenceClassification.from_pretrained("PatrickSchwabl/distilbert_fearspeech_classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c50785b50f42d77aec8a59b3f6bff14917f0a9628e79f1945501fcacda23821
- Size of remote file:
- 270 MB
- SHA256:
- 70ccb0e661419e401a51a9336279ccb82a5ed5bc379f1845becd3c7103763ec4
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