Flan-T5 and Flan-PaLM: instruction tuning scales to 1,800 tasks
In one sentence Google scales instruction tuning to 1,800 tasks and 540B parameters, open-sources Flan-T5, and proves that chain-of-thought reasoning is teachable via fine-tuning.
After 2021's FLAN — which used 60 task types — Google massively raised the bar: 1,800 different tasks, across many languages and formats. It's like going from a basic course to a full university curriculum.
The most important part for anyone using AI today is chain-of-thought: instead of just providing correct answers, the training data includes step-by-step reasoning. The model learns not just what to answer, but how to think through it.
Google then released Flan-T5, a family of models ranging from 80 million to 11 billion parameters, fully open. These models became the starting point for thousands of AI experiments and products because they work well and are small enough to run on ordinary hardware.
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