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@@ -28,7 +28,7 @@ We further pretrained XLMR/RoBERTa with InfoDCL framework by ([Zhang et al. 2023
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  Multilingual Model:
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  * InfoDCL-XLMR trained with multilingual TweetEmoji-multi: https://huggingface.co/UBC-NLP/InfoDCL-Emoji-XLMR-Base
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- Enlish Models:
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  * InfoDCL-RoBERTa trained with TweetEmoji-EN: https://huggingface.co/UBC-NLP/InfoDCL-emoji
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  * InfoDCL-RoBERTa trained with TweetHashtag-EN: https://huggingface.co/UBC-NLP/InfoDCL-hashtag
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  Multilingual Model:
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  * InfoDCL-XLMR trained with multilingual TweetEmoji-multi: https://huggingface.co/UBC-NLP/InfoDCL-Emoji-XLMR-Base
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+ English Models:
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  * InfoDCL-RoBERTa trained with TweetEmoji-EN: https://huggingface.co/UBC-NLP/InfoDCL-emoji
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  * InfoDCL-RoBERTa trained with TweetHashtag-EN: https://huggingface.co/UBC-NLP/InfoDCL-hashtag
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