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here Iamp;#39;m going to do a demo of how to fine tune a text-to-text generative model specifically the GPT Neo modeler from a Luther AI to create a text classifier weamp;#39;re going to try it with both the 125 million and 2.7 billion parameter versions weamp;#39;re going to use the student questions data which is a whole bunch of test questions about 120 000 of them although Iamp;#39;m going to only use about 5000 because we donamp;#39;t need that many for transfer learning and this is also going to take a very long time if we used all 120 000 of them now if I look at the data set we have here Iamp;#39;m going to take the top 18 lines of it which I know actually contain the information and we see here that itamp;#39;s a regular CSV where we have a text and a label now the text starts with the quote even though itamp;#39;s multi-line here so we have all the way up to this section and any Forest measure is afforestation and selective grazing clearing far selective felling and t