Instructions to use BornSaint/minimax-music3-latent-refiner-v0.10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BornSaint/minimax-music3-latent-refiner-v0.10 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BornSaint/minimax-music3-latent-refiner-v0.10", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
| import soundfile as sf | |
| import torch | |
| from minimax_music3_latent_refiner import MiniMaxMusic3RefinerPipeline | |
| audio, sample_rate = sf.read("input.wav", dtype="float32", always_2d=True) | |
| pipeline = MiniMaxMusic3RefinerPipeline.from_pretrained( | |
| "terminusresearch/minimax-music3-latent-refiner-v0.10", | |
| device="cuda", | |
| ) | |
| result = pipeline(torch.from_numpy(audio.T.copy()), sample_rate) | |
| sf.write("refined.wav", result.audio.squeeze(0).T.numpy(), result.sample_rate) | |