sandbox338/hatespeech

Swahili Hate Speech Classification Model

This is a fine-tuned BERT model for multi-class text classification in Swahili. It predicts whether a given text is:

• Non-hate speech
• Political hate speech
• Offensive language

🧠 Model Details

• Architecture: BERT (base)
• Languages: Swahili
• Classes: 3
• Model size: 178M parameters
• Framework: PyTorch
• Training data: A custom labeled dataset of Swahili social media or online comments (non-public)

🏷️ Labels

Label ID	Class Name
LABEL_0	Non-hate speech
LABEL_1	Political hate speech
LABEL_2	Offensive language

🚀 Usage

You can load and test the model using the transformers library:

from transformers import pipeline

classifier = pipeline("text-classification", model="sandbox338/hatespeech")

result = classifier("Hii ni ujumbe wa kawaida bila matusi.")
print(result)  # [{'label': 'LABEL_0', 'score': 0.98}]