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dysata
/
Wav2Vec2-Ru-Child

Automatic Speech Recognition
Transformers
Safetensors
Russian
wav2vec2
speech
russian
children
ctc
forced-alignment
pronunciation
phonetics
Model card Files Files and versions
xet
Community

Instructions to use dysata/Wav2Vec2-Ru-Child with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use dysata/Wav2Vec2-Ru-Child with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="dysata/Wav2Vec2-Ru-Child")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForCTC
    
    processor = AutoProcessor.from_pretrained("dysata/Wav2Vec2-Ru-Child")
    model = AutoModelForCTC.from_pretrained("dysata/Wav2Vec2-Ru-Child")
  • Notebooks
  • Google Colab
  • Kaggle
Wav2Vec2-Ru-Child
1.26 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 6 commits
dysata's picture
dysata
Update README.md
6a3e132 verified 2 months ago
  • .gitattributes
    1.52 kB
    initial commit 8 months ago
  • README.md
    4.35 kB
    Update README.md 2 months ago
  • added_tokens.json
    37 Bytes
    Upload 5 files 3 months ago
  • config.json
    2.39 kB
    Upload 2 files 3 months ago
  • model.safetensors
    1.26 GB
    xet
    Upload 2 files 3 months ago
  • preprocessor_config.json
    266 Bytes
    Upload 5 files 3 months ago
  • special_tokens_map.json
    102 Bytes
    Upload 5 files 3 months ago
  • tokenizer_config.json
    1.17 kB
    Upload 5 files 3 months ago
  • vocab.json
    484 Bytes
    Upload 5 files 3 months ago