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hf-internal-testing
/
processor_with_lm

Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
Model card Files Files and versions
xet
Community
1

Instructions to use hf-internal-testing/processor_with_lm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use hf-internal-testing/processor_with_lm with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="hf-internal-testing/processor_with_lm")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForCTC
    
    processor = AutoProcessor.from_pretrained("hf-internal-testing/processor_with_lm")
    model = AutoModelForCTC.from_pretrained("hf-internal-testing/processor_with_lm")
  • Notebooks
  • Google Colab
  • Kaggle
processor_with_lm
262 kB
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  • 1 contributor
History: 12 commits
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model
99281a1 verified about 2 years ago
  • language_model
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  • .gitattributes
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  • README.md
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  • alphabet.json
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  • config.json
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  • model.safetensors
    118 kB
    Adding `safetensors` variant of this model about 2 years ago
  • preprocessor_config.json
    166 Bytes
    Update preprocessor_config.json over 4 years ago
  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    140 kB
    xet
    fit vocab_size over 4 years ago
  • vocab.json
    148 Bytes
    up over 4 years ago