LocalLLaMA

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Community to discuss about Llama, the family of large language models created by Meta AI.

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Point me towards some basic dataset preparation tips for LLM's? (alien.top)

submitted 10 months ago by ArtifartX@alien.top to c/localllama@poweruser.forum

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I have some basic confusions over how to prepare a dataset for training. My plan is to use a model like llama2 7b chat, and train it on some proprietary data I have (in its raw format, this data is very similar to a text book). Do I need to find a way to reformat this large amount of text into a bunch of pairs like "query" and "output" ?

I have seen some LLM's which say things like "trained on Wikipedia" which seems like they were able to train it on that large chunk of text alone without reformatting it into data pairs - is there a way I can do that, too? Or since I want to target a chat model, I have to find a way to convert the data into pairs which basically serve as examples of proper input and output?

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[–] apssg96@alien.top 1 points 10 months ago

Very interesting topic. I have thought about this too. One idea that came to my mind was splitting your raw text into chunks, then ask a LLM to generate questions which the answers are these chunks and that way create an artificial dataset of QnA pairs. Of course the quality of the dataset relies on how well your structure your prompts to generate the questions.