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Trelis
/
Chorus-v1

Automatic Speech Recognition
Transformers
Safetensors
English
whisper
multi-speaker
chorus
Model card Files Files and versions
xet
Community

Instructions to use Trelis/Chorus-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Trelis/Chorus-v1 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="Trelis/Chorus-v1")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("Trelis/Chorus-v1")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("Trelis/Chorus-v1")
  • Notebooks
  • Google Colab
  • Kaggle
Chorus-v1
1.76 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 9 commits
RonanMcGovern's picture
RonanMcGovern
Add link for Trelis Multi-speaker Transcription
6c048a4 verified 23 days ago
  • .gitattributes
    1.52 kB
    initial commit 2 months ago
  • README.md
    7.91 kB
    Add link for Trelis Multi-speaker Transcription 23 days ago
  • added_tokens.json
    34.7 kB
    Add files using upload-large-folder tool 2 months ago
  • config.json
    1.23 kB
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  • generation_config.json
    3.77 kB
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  • merges.txt
    494 kB
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  • model.safetensors
    1.75 GB
    xet
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  • normalizer.json
    52.7 kB
    Add files using upload-large-folder tool 2 months ago
  • preprocessor_config.json
    357 Bytes
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  • special_tokens_map.json
    916 Bytes
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  • tokenizer.json
    3.93 MB
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  • tokenizer_config.json
    282 kB
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  • vocab.json
    836 kB
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