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Siyam
/
SKYLy

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
wav2vec2
Generated from Trainer
Model card Files Files and versions
xet
Metrics Training metrics Community
1

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

  • Libraries
  • Transformers

    How to use Siyam/SKYLy with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="Siyam/SKYLy")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForCTC
    
    processor = AutoProcessor.from_pretrained("Siyam/SKYLy")
    model = AutoModelForCTC.from_pretrained("Siyam/SKYLy", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
SKYLy
1.26 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 5 commits
Siyam's picture
Siyam
update model card README.md
2da92c3 over 4 years ago
  • runs
    End of training over 4 years ago
  • .gitattributes
    1.17 kB
    initial commit over 4 years ago
  • .gitignore
    13 Bytes
    Training in progress, step 400 over 4 years ago
  • README.md
    1.79 kB
    update model card README.md over 4 years ago
  • added_tokens.json
    23 Bytes
    add tokenizer over 4 years ago
  • config.json
    1.91 kB
    Training in progress, step 400 over 4 years ago
  • preprocessor_config.json
    214 Bytes
    Training in progress, step 400 over 4 years ago
  • pytorch_model.bin
    1.26 GB
    xet
    End of training over 4 years ago
  • special_tokens_map.json
    309 Bytes
    add tokenizer over 4 years ago
  • tokenizer_config.json
    260 Bytes
    add tokenizer over 4 years ago
  • training_args.bin
    2.8 kB
    xet
    Training in progress, step 400 over 4 years ago
  • vocab.json
    352 Bytes
    add tokenizer over 4 years ago