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Tejas2000
/
Wav2Vec_Deploy

Automatic Speech Recognition
Transformers
PyTorch
Marathi
wav2vec2
speech_to_text
audio
speech
xlsr-fine-tuning-week
Eval Results (legacy)
Model card Files Files and versions
xet
Community
1

Instructions to use Tejas2000/Wav2Vec_Deploy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Tejas2000/Wav2Vec_Deploy with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="Tejas2000/Wav2Vec_Deploy")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForCTC
    
    processor = AutoProcessor.from_pretrained("Tejas2000/Wav2Vec_Deploy")
    model = AutoModelForCTC.from_pretrained("Tejas2000/Wav2Vec_Deploy")
  • Notebooks
  • Google Colab
  • Kaggle
Wav2Vec_Deploy
1.26 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 8 commits
Tejas2000's picture
Tejas2000
Create vocab.json
e312b2f almost 3 years ago
  • .gitattributes
    1.48 kB
    initial commit almost 3 years ago
  • README.md
    4.95 kB
    Create README.md almost 3 years ago
  • config.json
    1.56 kB
    Create config.json almost 3 years ago
  • preprocessor_config.json
    157 Bytes
    Create preprocessor_config.json almost 3 years ago
  • pytorch_model.bin

    Detected Pickle imports (3)

    • "torch._utils._rebuild_tensor_v2",
    • "collections.OrderedDict",
    • "torch.FloatStorage"

    What is a pickle import?

    1.26 GB
    xet
    Upload pytorch_model.bin almost 3 years ago
  • special_tokens_map.json
    85 Bytes
    Create special_tokens_map.json almost 3 years ago
  • tokenizer_config.json
    138 Bytes
    Create tokenizer_config.json almost 3 years ago
  • vocab.json
    740 Bytes
    Create vocab.json almost 3 years ago