Text Classification
Transformers
Safetensors
PyTorch
English
roberta
hate-speech-detection
content-moderation
nlp
twitter
safety
offensive-language
Eval Results (legacy)
text-embeddings-inference
Instructions to use AuricErgeson/hate-speech-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AuricErgeson/hate-speech-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AuricErgeson/hate-speech-detector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AuricErgeson/hate-speech-detector") model = AutoModelForSequenceClassification.from_pretrained("AuricErgeson/hate-speech-detector") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7bf762aa98a49e83de5f52dca3542aa843dde1ea683badd1ebf2b5eaf1a60536
- Size of remote file:
- 5.2 kB
- SHA256:
- a2cc76cf9751090db9c83f5d9de5f7e7095c900581ede7aa0634ee809efc7488
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