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m-a-p
/
YuE2-Vae

Feature Extraction
Transformers
Safetensors
yue2_vae
audio
autoencoder
yue2
custom_code
Model card Files Files and versions
xet
Community

Instructions to use m-a-p/YuE2-Vae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use m-a-p/YuE2-Vae with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="m-a-p/YuE2-Vae", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("m-a-p/YuE2-Vae", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
YuE2-Vae
531 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
a43992899's picture
a43992899
Sync Suno v6 WildSongBench results and frontier figure
9a94e1d verified 5 days ago
  • assets
    Sync Suno v6 WildSongBench results and frontier figure 5 days ago
  • licenses
    Release YuE2-Vae 7 days ago
  • .gitattributes
    1.63 kB
    Release YuE2-Vae 7 days ago
  • LICENSE
    20.3 kB
    Release YuE2-Vae 7 days ago
  • README.md
    9.36 kB
    Sync Suno v6 WildSongBench results and frontier figure 5 days ago
  • THIRD_PARTY_NOTICES.md
    793 Bytes
    Release YuE2-Vae 7 days ago
  • config.json
    1.38 kB
    Release YuE2-Vae 7 days ago
  • model.safetensors
    531 MB
    xet
    Release YuE2-Vae 7 days ago
  • modeling_vae.py
    25.3 kB
    Release YuE2-Vae 7 days ago
  • weights_manifest.json
    178 Bytes
    Release YuE2-Vae 7 days ago