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MatricariaV
/
MMS-lm-without-replacements

Automatic Speech Recognition
Transformers
Safetensors
wav2vec2
Generated from Trainer
Model card Files Files and versions
xet
Community

Instructions to use MatricariaV/MMS-lm-without-replacements with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use MatricariaV/MMS-lm-without-replacements with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="MatricariaV/MMS-lm-without-replacements")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForCTC
    
    processor = AutoProcessor.from_pretrained("MatricariaV/MMS-lm-without-replacements")
    model = AutoModelForCTC.from_pretrained("MatricariaV/MMS-lm-without-replacements")
  • Notebooks
  • Google Colab
  • Kaggle
MMS-lm-without-replacements / language_model
617 MB
Ctrl+K
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  • 1 contributor
History: 1 commit

This model has 2 files scanned as unsafe.

MatricariaV's picture
MatricariaV
Upload lm-boosted decoder
b67d8c9 about 1 year ago
  • 5gram.bin
    603 MB
    xet
    Upload lm-boosted decoder about 1 year ago
  • attrs.json
    78 Bytes
    Upload lm-boosted decoder about 1 year ago
  • unigrams.txt
    13.6 MB
    xet
    Upload lm-boosted decoder about 1 year ago