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In section 3.6 of the OpenAI GPT-2 paper it mentions summarising text based relates to this, but the method is described in very high-level terms:

To induce summarization behavior we add the text TL;DR: after the article and generate 100 tokens with Top-k random sampling (Fan et al., 2018) with k=2 which reduces repetition and encourages more abstractive summaries than greedy decoding. We use the first 3 generated sentences in these 100 tokens as the summary.

Given a corpus of text, in concrete code terms (python preferred), how would I go about generating a summary of it?

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