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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AuricErgeson/hate-speech-detector") model = AutoModelForSequenceClassification.from_pretrained("AuricErgeson/hate-speech-detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from AuricErgeson/hate-speech-detector: direct link, hf CLI and curl.
- Browser
- Download file 3.56 MB
-
https://huggingface.co/AuricErgeson/hate-speech-detector/resolve/main/tokenizer.json
- Command line
-
hf download hf://AuricErgeson/hate-speech-detector/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/AuricErgeson/hate-speech-detector/resolve/main/tokenizer.json
3.56 MB
File too large to display, you can check the raw version instead.