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bezzam
/
VibeVoice-AcousticTokenizer

Feature Extraction
Transformers
Safetensors
vibevoice_acoustic_tokenizer
audio tokenizer
Model card Files Files and versions
xet
Community

Instructions to use bezzam/VibeVoice-AcousticTokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use bezzam/VibeVoice-AcousticTokenizer with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="bezzam/VibeVoice-AcousticTokenizer")
    # Load model directly
    from transformers import AutoFeatureExtractor, AutoModel
    
    extractor = AutoFeatureExtractor.from_pretrained("bezzam/VibeVoice-AcousticTokenizer")
    model = AutoModel.from_pretrained("bezzam/VibeVoice-AcousticTokenizer")
  • Notebooks
  • Google Colab
  • Kaggle
VibeVoice-AcousticTokenizer
1.37 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 27 commits
bezzam's picture
bezzam HF Staff
Update README.md
0bda44c verified 4 months ago
  • figs
    Upload tokenizer_comparison.png 6 months ago
  • .gitattributes
    1.52 kB
    initial commit 6 months ago
  • README.md
    6.66 kB
    Update README.md 4 months ago
  • config.json
    581 Bytes
    Upload model 4 months ago
  • model.safetensors
    1.37 GB
    xet
    Upload model 4 months ago
  • preprocessor_config.json
    274 Bytes
    Upload tokenizer 4 months ago