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techsword
/
wav2vec2-small-libri-scc-ft-ckp-10000

Feature Extraction
Transformers
Safetensors
wav2vec2
audio
Model card Files Files and versions
xet
Community
1

Instructions to use techsword/wav2vec2-small-libri-scc-ft-ckp-10000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use techsword/wav2vec2-small-libri-scc-ft-ckp-10000 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="techsword/wav2vec2-small-libri-scc-ft-ckp-10000")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoProcessor, AutoModel
    
    processor = AutoProcessor.from_pretrained("techsword/wav2vec2-small-libri-scc-ft-ckp-10000")
    model = AutoModel.from_pretrained("techsword/wav2vec2-small-libri-scc-ft-ckp-10000", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
wav2vec2-small-libri-scc-ft-ckp-10000
378 MB
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  • 1 contributor
History: 6 commits
techsword's picture
techsword
Add model card metadata (library, license, pipeline tag)
aaf5186 verified 2 months ago
  • .gitattributes
    1.48 kB
    initial commit over 3 years ago
  • README.md
    252 Bytes
    Add model card metadata (library, license, pipeline tag) 2 months ago
  • config.json
    2.4 kB
    Upload model over 3 years ago
  • model.safetensors
    378 MB
    xet
    Add model.safetensors (converted from pytorch_model.bin, verified bit-exact) 2 months ago
  • preprocessor_config.json
    159 Bytes
    Add preprocessor_config.json (Wav2Vec2FeatureExtractor, 16 kHz) so AutoProcessor/pipeline loading works 2 months ago