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TuKoResearch
/
WavCochV8192

Feature Extraction
Transformers
Safetensors
English
WavCoch.WavCoch
audio
speech
tokenizer
quantizer
cochlear
custom_code
Model card Files Files and versions
xet
Community

Instructions to use TuKoResearch/WavCochV8192 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use TuKoResearch/WavCochV8192 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="TuKoResearch/WavCochV8192", trust_remote_code=True)
    # Load model directly
    from transformers import AutoTokenizer
    model = AutoTokenizer.from_pretrained("TuKoResearch/WavCochV8192", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
WavCochV8192
44.3 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 77 commits
klemenk's picture
klemenk
Update modeling_wavcoch.py
4785b04 verified 4 months ago
  • .gitattributes
    1.52 kB
    initial commit about 1 year ago
  • README.md
    3.2 kB
    Update README.md 9 months ago
  • config.json
    613 Bytes
    Update config.json 9 months ago
  • configuration_wavcoch.py
    1.16 kB
    Update configuration_wavcoch.py about 1 year ago
  • model.safetensors
    44.3 MB
    xet
    Upload model.safetensors with huggingface_hub about 1 year ago
  • modeling_wavcoch.py
    30.2 kB
    Update modeling_wavcoch.py 4 months ago
  • tokenizer_config.json
    615 Bytes
    Update tokenizer_config.json about 1 year ago