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hts98
/
practice

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

Instructions to use hts98/practice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use hts98/practice with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="hts98/practice")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("hts98/practice")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("hts98/practice")
  • Notebooks
  • Google Colab
  • Kaggle
practice
3.09 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 4 commits
hts98's picture
hts98
Upload tokenizer
45d4991 almost 3 years ago
  • .gitattributes
    1.48 kB
    initial commit almost 3 years ago
  • added_tokens.json
    2.08 kB
    Upload tokenizer almost 3 years ago
  • config.json
    2.25 kB
    Upload WhisperForConditionalGeneration almost 3 years ago
  • generation_config.json
    1.27 kB
    Upload WhisperForConditionalGeneration almost 3 years ago
  • merges.txt
    494 kB
    Upload tokenizer almost 3 years ago
  • normalizer.json
    52.7 kB
    Upload tokenizer almost 3 years ago
  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    3.09 GB
    xet
    Upload WhisperForConditionalGeneration almost 3 years ago
  • special_tokens_map.json
    2.08 kB
    Upload tokenizer almost 3 years ago
  • tokenizer_config.json
    805 Bytes
    Upload tokenizer almost 3 years ago
  • vocab.json
    1.04 MB
    Upload tokenizer almost 3 years ago