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Figure 1: We ﬁnetune various language models on 1.8K tasks phrased as instructions, and evaluate them on unseen tasks.
We ﬁnetune both with and without exemplars (i.e., zero-shot and few-shot) and with and without chain-of-thought,
enabling generalization across a range of evaluation scenarios.

∗Equal contribution. Correspondence: lehou@google.com.
†Core contributor.
1Public checkpoints: https://github.com/google-research/t5x/blob/main/docs/models.md#flan-t5-checkpoints.

1
Scaling Instruction-Finetuned Language Models