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?
