MusicGen Melody 1.5B Audiocraft provides the code and models for MusicGen, a simple and controllable model for music generation. MusicGen is a single stage auto regressive Transformer model trained over a 32kHz EnCodec tokenizer with 4 codebooks sampled at 50 Hz. Unlike existing methods like MusicLM, MusicGen doesn't not require a self supervised semantic representation, and it generates all 4 codebooks in one pass. By introducing a small delay between the codebooks, we show we can predict them in parallel, thus having only 50 auto regressive steps per second of audio. MusicGen was published in Simple and Controllable Music Generation by Jade Copet, Felix Kreuk, Itai Gat, Tal Remez, David Kant, Gabriel Synnaeve, Yossi Adi, Alexandre Défossez . Four checkpoints are released: small medium large melody (this checkpoint) Example Try out MusicGen yourself! You can run MusicGen locally as well: 1. First install the audiocraft library 2. Make sure to have ffmpeg installed: 3. Run the following Python code: Model details Organization developing the model: The FAIR team of Meta AI. Model date: MusicGen was trained between April 2023 and May 2023. Model version: This is the version 1 of the…
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