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labhamlet
/
wavjepa-base

Feature Extraction
Transformers
Safetensors
wavjepa-base
audio
speech
waveform
custom_code
Model card Files Files and versions
xet
Community

Instructions to use labhamlet/wavjepa-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use labhamlet/wavjepa-base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="labhamlet/wavjepa-base", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("labhamlet/wavjepa-base", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
wavjepa-base
785 MB
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  • 1 contributor
History: 9 commits
GokseninYuksel's picture
GokseninYuksel
Upload model
6be4a50 verified 6 months ago
  • .gitattributes
    1.52 kB
    initial commit 6 months ago
  • README.md
    11.5 kB
    Update README.md 6 months ago
  • audio_extractor.py
    7.21 kB
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  • config.json
    1.12 kB
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  • configuration_wavjepa.py
    3.13 kB
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  • feature_extraction_wavjepa.py
    4 kB
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  • model.py
    8.11 kB
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  • model.safetensors
    785 MB
    xet
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  • modeling_wavjepa.py
    1.34 kB
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  • pos_embed.py
    10.6 kB
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  • preprocessor_config.json
    291 Bytes
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  • types.py
    1.51 kB
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  • utils.py
    1.25 kB
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