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waiv
/
FinVoc2Vec

Audio Classification
Transformers
Safetensors
English
finvoc2vec
feature-extraction
audio
classification
Wav2Vec2
sentiment
earnings conference calls
custom_code
Model card Files Files and versions
xet
Community

Instructions to use waiv/FinVoc2Vec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use waiv/FinVoc2Vec with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("audio-classification", model="waiv/FinVoc2Vec", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("waiv/FinVoc2Vec", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
FinVoc2Vec
1.27 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 9 commits
waiv's picture
waiv
Update Citation
63bac64 verified 8 months ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • README.md
    8.22 kB
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  • __init__.py
    134 Bytes
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  • config.json
    2.85 kB
    initial commit over 1 year ago
  • finvoc2vec_config.py
    365 Bytes
    initial commit over 1 year ago
  • finvoc2vec_model.py
    3.32 kB
    initial commit over 1 year ago
  • model.safetensors
    1.27 GB
    xet
    initial commit over 1 year ago
  • negative.mp3
    49.2 kB
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  • neutral.mp3
    60.4 kB
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  • positive.mp3
    103 kB
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  • preprocessor_config.json
    212 Bytes
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  • requirements.txt
    680 Bytes
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