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amharic_hate_speech_detection
Abel-Mek/amharic_hate_speech_detection
amharic_hate_speech_detection is a text classification model from Abel-Mek. Use it when you need a label for a piece of text. It is set up for transformers.
<h1Hate-Speech-Detection-in-Amharic-Language-mBERT</h1
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Jan 12, 2024
- Updated
- Jan 12, 2024
- SHA
- f32e2185
Model card
From the Hugging Face model README
<h1>Hate-Speech-Detection-in-Amharic-Language-mBERT</h1>
This Hugging Face model card contains a machine learning model that uses fine-tuned mBERT to detect hate speech in Amharic language. The model was fine-tuned using the Hugging Face Trainer API.
<h1>Fine-Tuning</h1>
This model was created by finetuning the mBERT model for the downstream task of Hate speech detection for the Amharic language. The initial mBERT model used for finetuning is http://Davlan/bert-base-multilingual-cased-finetuned-amharic which was provided by Davlan on Huggingface.
<h1>Usage</h1>
You can use the model through the Hugging Face Transformers library, either by directly loading the model in your Python code or by using the Hugging Face model hub.
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Languages
- am
- Created
- Jan 12, 2024
- Updated
- Jan 12, 2024