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esb
/
wav2vec2-ctc-pretrained

Feature Extraction
Transformers
JAX
wav2vec2
Model card Files Files and versions
xet
Community

Instructions to use esb/wav2vec2-ctc-pretrained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use esb/wav2vec2-ctc-pretrained with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="esb/wav2vec2-ctc-pretrained")
    # Load model directly
    from transformers import AutoProcessor, AutoModel
    
    processor = AutoProcessor.from_pretrained("esb/wav2vec2-ctc-pretrained")
    model = AutoModel.from_pretrained("esb/wav2vec2-ctc-pretrained")
  • Notebooks
  • Google Colab
  • Kaggle
wav2vec2-ctc-pretrained
1.26 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
Sanchit Gandhi
Add pretrained weights
a341c6c over 3 years ago
  • .gitattributes
    1.38 kB
    Add pretrained weights over 3 years ago
  • config.json
    2.06 kB
    Add pretrained weights over 3 years ago
  • flax_model.msgpack
    1.26 GB
    xet
    Add pretrained weights over 3 years ago
  • preprocessor_config.json
    256 Bytes
    Add pretrained weights over 3 years ago
  • special_tokens_map.json
    85 Bytes
    Add pretrained weights over 3 years ago
  • tokenizer_config.json
    588 Bytes
    Add pretrained weights over 3 years ago
  • vocab.json
    291 Bytes
    Add pretrained weights over 3 years ago