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bond005
/
wav2vec2-mbart50-ru

Automatic Speech Recognition
Transformers
PyTorch
Russian
speech-encoder-decoder
audio
speech
common_voice
SberDevices/Golos
sova_rudevices
rulibrispeech
Eval Results (legacy)
Model card Files Files and versions
xet
Community
1

Instructions to use bond005/wav2vec2-mbart50-ru with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use bond005/wav2vec2-mbart50-ru with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="bond005/wav2vec2-mbart50-ru")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq
    
    tokenizer = AutoTokenizer.from_pretrained("bond005/wav2vec2-mbart50-ru")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("bond005/wav2vec2-mbart50-ru", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
wav2vec2-mbart50-ru
3.19 GB
Ctrl+K
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  • 1 contributor
History: 14 commits
bond005's picture
bond005
Update README.md
e6ff511 over 3 years ago
  • .gitattributes
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  • README.md
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  • config.json
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  • preprocessor_config.json
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  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    3.17 GB
    xet
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  • sentencepiece.bpe.model
    5.07 MB
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  • special_tokens_map.json
    880 Bytes
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  • test_sound.wav
    226 kB
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  • tokenizer.json
    17.1 MB
    xet
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  • tokenizer_config.json
    1.39 kB
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