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rossevine
/
Model_S_P_Wav2Vec2_Versi2

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
wav2vec2
Generated from Trainer
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use rossevine/Model_S_P_Wav2Vec2_Versi2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use rossevine/Model_S_P_Wav2Vec2_Versi2 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="rossevine/Model_S_P_Wav2Vec2_Versi2")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForCTC
    
    processor = AutoProcessor.from_pretrained("rossevine/Model_S_P_Wav2Vec2_Versi2")
    model = AutoModelForCTC.from_pretrained("rossevine/Model_S_P_Wav2Vec2_Versi2")
  • Notebooks
  • Google Colab
  • Kaggle
Model_S_P_Wav2Vec2_Versi2 / language_model
6.19 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
rossevine's picture
rossevine
Upload lm-boosted decoder
3d6592a over 2 years ago
  • 5gram.bin
    2.02 GB
    xet
    Upload lm-boosted decoder over 2 years ago
  • 5gram_correct.arpa
    4.16 GB
    xet
    Upload lm-boosted decoder over 2 years ago
  • attrs.json
    78 Bytes
    Upload lm-boosted decoder over 2 years ago
  • unigrams.txt
    6.47 MB
    Upload lm-boosted decoder over 2 years ago