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mlr2000
/
vocoder-small

Text-to-Speech
Transformers
Safetensors
hifi_gan
feature-extraction
audio
vocoder
hifi-gan
bigvgan
neural-vocoder
speaker-conditioning
audio-watermarking
custom_code
Model card Files Files and versions
xet
Community

Instructions to use mlr2000/vocoder-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use mlr2000/vocoder-small with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-to-speech", model="mlr2000/vocoder-small", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("mlr2000/vocoder-small", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
vocoder-small
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  • 1 contributor
History: 2 commits
mlr2000's picture
mlr2000
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  • .gitattributes
    1.52 kB
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  • README.md
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  • __init__.py
    183 Bytes
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  • alias_free_act.py
    836 Bytes
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  • alias_free_filter.py
    3.4 kB
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  • alias_free_resample.py
    1.85 kB
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  • bigvgan_activations.py
    4.6 kB
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  • bigvgan_model.py
    12.8 kB
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  • config.json
    3.07 kB
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  • configuration_hifigan.py
    7.87 kB
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  • example_roundtrip.ipynb
    5 kB
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  • model.safetensors
    57.2 MB
    xet
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  • modeling_hifigan.py
    5.91 kB
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  • speaker_embedding_config.py
    1.25 kB
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  • temporal_adapter.py
    4.28 kB
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