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hf-internal-testing
/
tiny-random-unispeech

Audio Classification
Transformers
PyTorch
ONNX
Safetensors
unispeech
Model card Files Files and versions
xet
Community
3

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

  • Libraries
  • Transformers

    How to use hf-internal-testing/tiny-random-unispeech with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("audio-classification", model="hf-internal-testing/tiny-random-unispeech")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForAudioClassification
    
    processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-unispeech")
    model = AutoModelForAudioClassification.from_pretrained("hf-internal-testing/tiny-random-unispeech")
  • Notebooks
  • Google Colab
  • Kaggle
tiny-random-unispeech
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  • 4 contributors
History: 5 commits
ArthurZ's picture
ArthurZ HF Staff
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model (#3)
3ee5cca verified 6 months ago
  • onnx
    Upload ONNX weights (#2) almost 2 years ago
  • .gitattributes
    1.18 kB
    initial commit over 4 years ago
  • config.json
    1.69 kB
    up over 4 years ago
  • model.safetensors
    137 kB
    Adding `safetensors` variant of this model (#3) 6 months ago
  • preprocessor_config.json
    215 Bytes
    up over 4 years ago
  • pytorch_model.bin
    159 kB
    xet
    up over 4 years ago
  • special_tokens_map.json
    85 Bytes
    up over 4 years ago
  • tokenizer_config.json
    554 Bytes
    up over 4 years ago
  • vocab.json
    291 Bytes
    up over 4 years ago