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mau-cr
/
mayan_best_model

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

Instructions to use mau-cr/mayan_best_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use mau-cr/mayan_best_model with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="mau-cr/mayan_best_model")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForCTC
    
    processor = AutoProcessor.from_pretrained("mau-cr/mayan_best_model")
    model = AutoModelForCTC.from_pretrained("mau-cr/mayan_best_model")
  • Notebooks
  • Google Colab
  • Kaggle
mayan_best_model
3.86 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
mau-cr's picture
mau-cr
Add processor with LM (KenLM 3-gram decoder)
2a9ec8f verified 4 days ago
  • language_model
    Add processor with LM (KenLM 3-gram decoder) 4 days ago
  • .gitattributes
    1.52 kB
    initial commit 4 days ago
  • README.md
    5.17 kB
    Upload Wav2Vec2ForCTC 4 days ago
  • added_tokens.json
    30 Bytes
    Add processor with LM (KenLM 3-gram decoder) 4 days ago
  • alphabet.json
    258 Bytes
    Add processor with LM (KenLM 3-gram decoder) 4 days ago
  • config.json
    2 kB
    Upload Wav2Vec2ForCTC 4 days ago
  • model.safetensors
    3.86 GB
    xet
    Upload Wav2Vec2ForCTC 4 days ago
  • processor_config.json
    305 Bytes
    Add processor with LM (KenLM 3-gram decoder) 4 days ago
  • tokenizer_config.json
    1.21 kB
    Add processor with LM (KenLM 3-gram decoder) 4 days ago
  • vocab.json
    490 Bytes
    Add processor with LM (KenLM 3-gram decoder) 4 days ago