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ales
/
whisper-tiny-be-test

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Belarusian
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Model card Files Files and versions
xet
Metrics Training metrics Community
1

Instructions to use ales/whisper-tiny-be-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ales/whisper-tiny-be-test with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="ales/whisper-tiny-be-test")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("ales/whisper-tiny-be-test")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("ales/whisper-tiny-be-test")
  • Notebooks
  • Google Colab
  • Kaggle
whisper-tiny-be-test / src
41.3 kB
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  • 1 contributor
History: 7 commits
ales's picture
ales
Training in progress, step 310
1404413 over 3 years ago
  • readme.md
    7.6 kB
    Training in progress, step 310 over 3 years ago
  • requirements.txt
    171 Bytes
    Training in progress, step 310 over 3 years ago
  • run.sh
    1.19 kB
    Training in progress, step 310 over 3 years ago
  • run_debug.sh
    1.19 kB
    Training in progress, step 310 over 3 years ago
  • run_speech_recognition_seq2seq_streaming.py
    30.4 kB
    Training in progress, step 210 over 3 years ago
  • setup_env.sh
    706 Bytes
    Training in progress, step 310 over 3 years ago