# How I fine-tune BART for summarization using large texts?

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**Category:** Research\
**Created:** [September 27, 2020, 4:02am UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fhow-i-fine-tune-bart-for-summarization-using-large-texts%2F1266 "2020-09-27T04:02:21Z")\
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**Author:** ![valhalla](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/valhalla/32/4179_2.png) [@valhalla](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fvalhalla)%5C
**Post date:** [September 27, 2020, 7:00am UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fhow-i-fine-tune-bart-for-summarization-using-large-texts%2F1266%2F2 "2020-09-27T07:00:53Z")

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Hi, there’e already thread for this, you might find it helpful

> [@Summarization on long documents](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fsummarization-on-long-documents%2F920%2F2)%3A
>
> You can try extractive summarisation followed by abstractive. In the extractive step you choose top k sentences of which you choose top n allowed till model max length. Another way is to use successive abstractive summarisation where you summarise in chunk of model max length and then again use it to summarise till the length you want. This method will be super expensive. You can also combine first + second method.

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