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techsword
/
wav2vec2-base-fsc-ic-multiheadmultilabel

Audio Classification
Transformers
Safetensors
English
wav2vec2multihead_3class
speech
speech classification
intent classification
custom_code
Model card Files Files and versions
xet
Community

Instructions to use techsword/wav2vec2-base-fsc-ic-multiheadmultilabel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use techsword/wav2vec2-base-fsc-ic-multiheadmultilabel with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("audio-classification", model="techsword/wav2vec2-base-fsc-ic-multiheadmultilabel", trust_remote_code=True)
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoModelForAudioClassification
    model = AutoModelForAudioClassification.from_pretrained("techsword/wav2vec2-base-fsc-ic-multiheadmultilabel", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
wav2vec2-base-fsc-ic-multiheadmultilabel
378 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 10 commits
techsword's picture
techsword
Unify license to Apache-2.0 (matches base model facebook/wav2vec2-base)
08ddf7e verified about 2 months ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • README.md
    5.55 kB
    Unify license to Apache-2.0 (matches base model facebook/wav2vec2-base) about 2 months ago
  • config.json
    3.64 kB
    Upload Wav2Vec2ForMultiHeadMultiLabelClassification over 1 year ago
  • configuration_wav2vec2multihead.py
    501 Bytes
    Upload Wav2Vec2ForMultiHeadMultiLabelClassification over 1 year ago
  • model.safetensors
    378 MB
    xet
    Upload Wav2Vec2ForMultiHeadMultiLabelClassification over 1 year ago
  • modeling_wav2vec2multihead.py
    3.62 kB
    Upload Wav2Vec2ForMultiHeadMultiLabelClassification over 1 year ago
  • preprocessor_config.json
    159 Bytes
    Add preprocessor_config.json (Wav2Vec2FeatureExtractor, 16 kHz) so AutoProcessor/pipeline loading works about 2 months ago