Audience
AI developers interested in a powerful large language model
About T5
With T5, we propose reframing all NLP tasks into a unified text-to-text-format where the input and output are always text strings, in contrast to BERT-style models that can only output either a class label or a span of the input. Our text-to-text framework allows us to use the same model, loss function, and hyperparameters on any NLP task, including machine translation, document summarization, question answering, and classification tasks (e.g., sentiment analysis). We can even apply T5 to regression tasks by training it to predict the string representation of a number instead of the number itself.
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Integrations
Company Information
Google
Founded: 1998
United States
ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html
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