Instructions to use OzzyGT/YuE2-Modular with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use OzzyGT/YuE2-Modular with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("OzzyGT/YuE2-Modular", 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
YuE2 Modular Diffusers
A 69-second song generated with the code below, seed 831001.
Modular Diffusers blocks for m-a-p/YuE2-3B: full songs from a style description and lyrics, planned as an ABC score first, as 48 kHz stereo audio. The model code and weights are in OzzyGT/YuE2-3B-Diffusers.
Note: This model requires tiktoken and the example uses soundfile, install them with pip install tiktoken soundfile.
Licensing
The code is Apache-2.0, adapted from multimodal-art-projection/YuE. The weights are CC BY-NC 4.0 (non-commercial); see the model repository.
Sample song
The song above was generated with the following code:
import soundfile as sf
import torch
from diffusers import ModularPipelineBlocks
blocks = ModularPipelineBlocks.from_pretrained( # load the blocks first to avoid warnings
"OzzyGT/YuE2-Modular",
trust_remote_code=True,
components_repo="OzzyGT/YuE2-3B-Diffusers",
trust_components_code=True,
)
pipe = blocks.init_pipeline()
pipe.load_components(dtype={"transformer": torch.bfloat16, "vae": torch.float32})
pipe.to("cuda")
style = "English, warm piano pop, expressive female voice, acoustic piano, rounded bass and light drums, lyrical memorable melody, unhurried phrasing, 88 BPM"
lyrics = """[Verse]
Neon fades along the lane
Footsteps keep the time of rain
Fold the night and leave it here
Morning has a sky to clear
[Chorus]
Let the day come into view
Every road begins with you
Hold a little room for light
We will sing beyond the night"""
state = pipe(style=style, lyrics=lyrics, seed=831001, use_cuda_graph=True)
sf.write("song.flac", state.get("audios")[0].T.numpy(), state.get("sample_rate"), subtype="PCM_24")
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Model tree for OzzyGT/YuE2-Modular
Base model
m-a-p/YuE2-3B