Name:
Description: Creates grooves based on the rhythm of any input. Can be used to generate a drum accompaniment to a bassline or melody, or to create a drum track from a tapped rhythm. Drumify works best with performed inputs, but it can also handle quantized clips. Ready to use as a Max for Live device. If you want to train the model on your own data or try different pre-trained models provided by the Magenta team, refer to the instructions on the team's GitHub page: https://github.com/magenta/magenta/tree/main/magenta/models/drums_rnn
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Website:
Input types: Audio MIDI Text None Genre Metadata Image
Output types: Audio MIDI
Output length:
Technology: Not Specified Latent Consistency Model Latent Diffusion LSTM VAE Sequence-to-sequence neural network Transformer Suite of AI tools Diffusion Hierarchical Recurrent Neural Network (RNN) Autoregressive Convolutional Neural Network
Dataset:
License type:
Has real time inference: Yes No Not known
Is free: Yes No Yes and No, depending on the plan Not known
Is open source: Yes No Not known
Are checkpoints available: Yes No Not known
Can finetune: Yes No Not known
Can train from scratch: Yes No Not known
Tags: text-to-audio MIDI text-prompt small-dataset open-source low-resource free checkpoints proprietary no-input image-to-audio API
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