データの前処理、トークン化、モデルの訓練と推論を含む、完全な機械学習パイプラインが提示されます。提示されたシステムは、Large Piano Modelsとの音楽的な相互作用を通じて作成された複数の生成例をデモンストレーションするために使用されます。
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This talk presents a methodology for working with very large, GPT-like deep learning models trained on (open and ethically sourced) MIDI data. This approach promotes nuanced, musical interfacing with the model, requiring practice and skill development instead of one-shot text-based prompting.
The full machine-learning pipeline is presented, including data pre-processing, tokenization, model training and inference. The presented system will be used to demonstrate multiple generative examples created through musical interaction with Large Piano Models.
