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  # Multilingual PL-BERT checkpoint
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- The checkpoint open-sourced here is trained by Papercup using the open-source PL-BERT model found here https://github.com/yl4579/PL-BERT. It is trained to be supported by StyleTTS2, which can be found here: https://github.com/yl4579/StyleTTS2. See below for the languages that it has been trained on (the languages correspond to the crowdsourced dataset found here https://huggingface.co/datasets/styletts2-community/multilingual-phonemes-10k-alpha).
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  Notable differences compared to the default PL-BERT checkpoint and config available [here](https://github.com/yl4579/StyleTTS2/tree/main/Utils/PLBERT):
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  * Because we are working with many languages, we are using a different tokenizer now: `bert-base-multilingual-cased`.
 
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  # Multilingual PL-BERT checkpoint
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+ The checkpoint open-sourced here is trained by Papercup using the open-source PL-BERT model found here https://github.com/yl4579/PL-BERT. It is trained to be supported by StyleTTS2, which can be found here: https://github.com/yl4579/StyleTTS2. You can see in the model card the languages that it has been trained on (the languages correspond to the crowdsourced dataset found here https://huggingface.co/datasets/styletts2-community/multilingual-phonemes-10k-alpha).
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  Notable differences compared to the default PL-BERT checkpoint and config available [here](https://github.com/yl4579/StyleTTS2/tree/main/Utils/PLBERT):
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  * Because we are working with many languages, we are using a different tokenizer now: `bert-base-multilingual-cased`.