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GleamEyeBeast
/
ascend_with_timit

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 GleamEyeBeast/ascend_with_timit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use GleamEyeBeast/ascend_with_timit with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="GleamEyeBeast/ascend_with_timit")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForCTC
    
    processor = AutoProcessor.from_pretrained("GleamEyeBeast/ascend_with_timit")
    model = AutoModelForCTC.from_pretrained("GleamEyeBeast/ascend_with_timit")
  • Notebooks
  • Google Colab
  • Kaggle
ascend_with_timit
1.28 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 6 commits
GleamEyeBeast's picture
GleamEyeBeast
update model card README.md
913fa7f about 4 years ago
  • runs
    End of training about 4 years ago
  • .gitattributes
    1.22 kB
    initial commit about 4 years ago
  • .gitignore
    13 Bytes
    Training in progress, step 500 about 4 years ago
  • README.md
    1.66 kB
    update model card README.md about 4 years ago
  • config.json
    2.28 kB
    Training in progress, step 500 about 4 years ago
  • preprocessor_config.json
    256 Bytes
    add model about 4 years ago
  • pytorch_model.bin
    1.28 GB
    xet
    End of training about 4 years ago
  • special_tokens_map.json
    85 Bytes
    add model about 4 years ago
  • tokenizer_config.json
    257 Bytes
    add model about 4 years ago
  • training_args.bin
    2.99 kB
    xet
    Training in progress, step 500 about 4 years ago
  • vocab.json
    45.8 kB
    add model about 4 years ago