Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

Hcask
/
distilhubert

Audio Classification
Transformers
TensorBoard
Safetensors
hubert
Generated from Trainer
Eval Results (legacy)
Model card Files Files and versions
xet
Metrics Training metrics Community

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

  • Libraries
  • Transformers

    How to use Hcask/distilhubert with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("audio-classification", model="Hcask/distilhubert")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForAudioClassification
    
    processor = AutoProcessor.from_pretrained("Hcask/distilhubert")
    model = AutoModelForAudioClassification.from_pretrained("Hcask/distilhubert")
  • Notebooks
  • Google Colab
  • Kaggle
distilhubert / runs
104 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 15 commits
Hcask's picture
Hcask
End of training
02acc07 verified about 1 year ago
  • Mar10_20-59-25_37b1317acf0d
    End of training about 1 year ago
  • Mar10_21-14-45_37b1317acf0d
    End of training about 1 year ago
  • Mar11_13-58-32_2dae0ebb4030
    Training in progress, epoch 1 about 1 year ago
  • May05_13-17-17_e4172518e05d
    End of training about 1 year ago