Building an LLM fine-tuning Dataset
827Going through the building of a QLoRA fine-tuning dataset for a language model.
NVIDIA GTC signup: https://nvda.ws/3XTqlB6
Fine-tuning code: https://github.com/Sentdex/LLM-Finetuning
5000-step Walls1337bot adapter: https://huggingface.co/Sentdex/Walls1337bot-Llama2-7B-003.005.5000
WSB Dataset: https://huggingface.co/datasets/Sentdex/WSB-003.005
"I have every reddit comment" original reddit post and torrent info: https://www.reddit.com/r/datasets/comments/3bxlg7/i_have_every_publicly_available_reddit_comment/
2007-2015 Reddit Archive.org: https://archive.org/download/2015_reddit_comments_corpus/reddit_data/
Reddit BigQuery 2007-2019 (this has other data besides reddit comments too!): https://reddit.com/r/bigquery/comments/3cej2b/17_billion_reddit_comments_loaded_on_bigquery/
Contents:
0:00 - Introduction to Dataset building for fine-tuning.
02:53 - The Reddit dataset options (Torrent, Archive.org, BigQuery)
06:07 - Exporting BigQuery Reddit (and some other data)
14:44 - Decompressing all of the gzip archives
25:13 - Re-combining the archives for target subreddits
28:29 - How to structure the data
40:40 - Building training samples and saving to database
48:49 - Creating customized training json files
54:11 - QLoRA training and results
Neural Networks from Scratch book: https://nnfs.io
Channel membership: https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ/join
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Reddit: https://www.reddit.com/r/sentdex/
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