Task
Text Classification
I
Hate-speech-CNERG/indic-abusive-allInOne-MuRIL
Text Classification·Hate-speech-CNERG· 78.3K· 5
This model is used detecting abusive speech in Bengali, Devanagari Hindi, Code-mixed Hindi, Code-mixed Kannada, Code-mixed Malayalam, Marathi, Code-mixed Tamil, Urdu, Code-mixed Urdu, and English languages. The allInOne in the name refers to the Joint training/Cross-lingual training, where the model is trained using all the languages data. It is finetuned on MuRIL model. The model is trained with
# pull & run locally
pip install mlforge-sdk && mlforge pull Hate-speech-CNERG/indic-abusive-allInOne-MuRIL
pip install mlforge-sdk && mlforge pull Hate-speech-CNERG/indic-abusive-allInOne-MuRIL
Model details
Provider
Hate-speech-CNERG
Framework
transformers
Parameters
237.6M
Size
1.8 GB
License
afl-3.0
Downloads
78.3K
Likes
5
Paper
arXiv:2204.12543
Updated
2023-11-02
About Hate-speech-CNERG/indic-abusive-allInOne-MuRIL
This model is used detecting abusive speech in Bengali, Devanagari Hindi, Code-mixed Hindi, Code-mixed Kannada, Code-mixed Malayalam, Marathi, Code-mixed Tamil, Urdu, Code-mixed Urdu, and English languages. The allInOne in the name refers to the Joint training/Cross-lingual training, where the model is trained using all the languages data. It is finetuned on MuRIL model. The model is trained with learning rates of 2e-5. Training code can be found at this url
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