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@@ -79,6 +79,8 @@ These models can be used for Arabic natural language understanding tasks where p
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  - Dialect identification
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  - Pronunciation-sensitive applications
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  ## Bias, Risks, and Limitations
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  The models are trained on Wikipedia data, which may not represent all varieties of Arabic equally. The diacritization process, while state-of-the-art, may introduce some errors or biases in the training data.
 
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  - Dialect identification
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  - Pronunciation-sensitive applications
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+ For examples on how these models can be used in code, take a look at: https://github.com/Fadi987/StyleTTS2/blob/main/Utils/PLBERT/util.py
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  ## Bias, Risks, and Limitations
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  The models are trained on Wikipedia data, which may not represent all varieties of Arabic equally. The diacritization process, while state-of-the-art, may introduce some errors or biases in the training data.