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Stas Bekman authored
* [examples/seq2seq] fix t5 examples This PR: * fixes T5 examples to include `--source_prefix` - it's **not** optional. If you give it a try you will see that you get 10x worse bleu scores w/o it. w/ `27.6849`, w/ `2.374` * added a normal translation example w/o the peculiarities of MBart and T5 * reduces the default max samples to 50 so it's much faster to test quickly summarization seems to be broken for t5 score-wise: https://github.com/huggingface/transformers/issues/10733 @sgugger * specify explicitly the t5 models requiring the special handling * one more * update the t5 summarization example to use cnn_dailymail * move max*samples into the top level README.md * better wording * better wording
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