Music Generation Finetuning notebook using the Meta's MusicGen model, trained on music from the Violet Evergarden: Automemories Soundtrack. Code is modified to run on AWS Sagemaker & partially on M1 Apple Silicon (no GPU).
- AWS Sagemaker (Compute/Jupyter Notebooks platform)
- Weights & Biases (ML Observability)
- Musicgen (Checkpoint Model for Music Generation)
- aprilschen/VioletEvergardenAutomemories (dataset)
- huggingface/transformers
- Ipython (Audio displays)
- demucs (Voice removal)
- librosa (labelling: tempo and key)
- CLAP (labelling: genre, instrument, mood)
- Perameter-Efficient Fine-Tuning (Low-Rank Adaptation library)
Inspiration for training code taken from various Github users, including lyramakesmusic, sakemin, and ylacombe.