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bert-japanese-finetuned-sentiment

The model "bert-japanese-finetuned-sentiment" is a text classification model that has been fine-tuned specifically for sentiment analysis on Japanese text. It is based on the BERT (Bidirectional Encoder Representations from Transformers) architecture, which is a popular model for natural language understanding tasks. The model has been pre-trained on a large corpus of Japanese text and then fine-tuned on a sentiment analysis task using labeled data. It can be used to classify Japanese text into positive, negative, or neutral sentiment categories.

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