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mispeech
/
ced-base

Audio Classification
Transformers
ONNX
Safetensors
ced
custom_code
Model card Files Files and versions
xet
Community
1

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

  • Libraries
  • Transformers

    How to use mispeech/ced-base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("audio-classification", model="mispeech/ced-base", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModelForAudioClassification
    model = AutoModelForAudioClassification.from_pretrained("mispeech/ced-base", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
ced-base
430 MB
Ctrl+K
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  • 2 contributors
History: 24 commits
richermans's picture
richermans
Update configuration_ced.py
db3e14a verified about 1 month ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    3.41 kB
    Update README.md about 2 months ago
  • config.json
    25.1 kB
    Update config.json 11 months ago
  • configuration_ced.py
    6.75 kB
    Update configuration_ced.py about 1 month ago
  • feature_extraction_ced.py
    6.48 kB
    Upload 3 files 11 months ago
  • model.onnx
    86.9 MB
    xet
    Uploaded model.onnx ( 8 bit int ) about 2 months ago
  • model.safetensors
    343 MB
    xet
    Upload CedForAudioClassification over 2 years ago
  • modeling_ced.py
    20.2 kB
    Update modeling_ced.py 2 months ago
  • preprocessor_config.json
    384 Bytes
    Update preprocessor_config.json 11 months ago