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qqjz
/
WhisperPro

Automatic Speech Recognition
Transformers
Safetensors
English
whisper
textpro-slm
prosody
speech
audio
original-checkpoint
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use qqjz/WhisperPro with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="qqjz/WhisperPro")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoProcessor, WhisperSpeechCodecEncoder
    
    processor = AutoProcessor.from_pretrained("qqjz/WhisperPro")
    model = WhisperSpeechCodecEncoder.from_pretrained("qqjz/WhisperPro", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
WhisperPro
3.22 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
qqjz's picture
qqjz
Release verified original checkpoint artifacts
28c2766 verified 1 day ago
  • .gitattributes
    1.52 kB
    initial commit 1 day ago
  • LICENSE
    11.3 kB
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  • NOTICE
    226 Bytes
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  • README.md
    4.12 kB
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  • SHA256SUMS.json
    1.81 kB
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  • added_tokens.json
    34.6 kB
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  • codec_config.json
    30 Bytes
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  • config.json
    1.22 kB
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  • generation_config.json
    3.85 kB
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  • merges.txt
    494 kB
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  • model.safetensors
    3.22 GB
    xet
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  • normalizer.json
    52.7 kB
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  • preprocessor_config.json
    340 Bytes
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  • special_tokens_map.json
    2.07 kB
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  • tokenizer_config.json
    283 kB
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  • vocab.json
    1.04 MB
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