The original GPT4All model was trained with around one million prompt-response pairs collected from various datasets, followed by extensive curation to enhance data quality.
After removing non-ideal responses, we finalized our dataset with 437,605 prompt-response pairs, focusing on quality over quantity, enhancing the model's training efficacy.
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