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  # TL;DR
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- If you already know T5, FLAN-T5 is just better at everything! It is a **bigger model (+ XX parameters)** was trained on **more tasks (+ XX )**, **more data (+ XX tokens)** and **more languags (+ XX languages)**. As mentioned in the first few lines of the abstract :
 
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  > Flan-PaLM 540B achieves state-of-the-art performance on several benchmarks, such as 75.2% on five-shot MMLU. We also publicly release Flan-T5 checkpoints,1 which achieve strong few-shot performance even compared to much larger models, such as PaLM 62B. Overall, instruction finetuning is a general method for improving the performance and usability of pretrained language models.
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  **Disclaimer**: Content from **this** model card has been written by the Hugging Face team, and parts of it were copy pasted from the [T5 model card](https://huggingface.co/t5-large).
 
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  # TL;DR
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+ If you already know T5, FLAN-T5 is just better at everything.
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+ As mentioned in the first few lines of the abstract :
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  > Flan-PaLM 540B achieves state-of-the-art performance on several benchmarks, such as 75.2% on five-shot MMLU. We also publicly release Flan-T5 checkpoints,1 which achieve strong few-shot performance even compared to much larger models, such as PaLM 62B. Overall, instruction finetuning is a general method for improving the performance and usability of pretrained language models.
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  **Disclaimer**: Content from **this** model card has been written by the Hugging Face team, and parts of it were copy pasted from the [T5 model card](https://huggingface.co/t5-large).