Text Classification
Transformers
PyTorch
Safetensors
English
deberta
Trained with AutoTrain
social
offensive speech detection
moderation
Instructions to use KoalaAI/HateSpeechDetector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KoalaAI/HateSpeechDetector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KoalaAI/HateSpeechDetector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KoalaAI/HateSpeechDetector") model = AutoModelForSequenceClassification.from_pretrained("KoalaAI/HateSpeechDetector") - Notebooks
- Google Colab
- Kaggle
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README.md
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The model is fine-tuned on the tweet_eval dataset, which consists of seven heterogeneous tasks in Twitter, all framed as multi-class tweet classification. The 'hate' subset is used for this task.
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This model is part of our series in moderation models, which includes the following other models that may be of interest to you:
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We believe these models can be used in tandem to support one another and thus build a more robust moderation tool, for example.
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The model is fine-tuned on the tweet_eval dataset, which consists of seven heterogeneous tasks in Twitter, all framed as multi-class tweet classification. The 'hate' subset is used for this task.
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This model is part of our series in moderation models, which includes the following other models that may be of interest to you:
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* [Offensive Speech Detector](https://huggingface.co/KoalaAI/OffensiveSpeechDetector)
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We believe these models can be used in tandem to support one another and thus build a more robust moderation tool, for example.
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