Text Classification
Transformers
Safetensors
Moroccan Arabic
Arabic
bert
toxicity-detection
content-moderation
offensive-language
moroccan-darija
darija
low-resource-languages
Eval Results (legacy)
text-embeddings-inference
Instructions to use TypicaAI/DarijaToxicityDetector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TypicaAI/DarijaToxicityDetector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TypicaAI/DarijaToxicityDetector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TypicaAI/DarijaToxicityDetector") model = AutoModelForSequenceClassification.from_pretrained("TypicaAI/DarijaToxicityDetector") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a6eca7c7a7ecb1b31d6738b2c1bcdf6b3907fba6a07387a1cdd19b226086031c
- Size of remote file:
- 590 MB
- SHA256:
- b48723fb93a332f39396101e359df62e48da4af91827fa6e26a30b6ddd104957
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