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

Kleber
/
output_dir

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Kinyarwanda
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Model card Files Files and versions
xet
Metrics Training metrics Community
1

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

  • Libraries
  • Transformers

    How to use Kleber/output_dir with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="Kleber/output_dir")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("Kleber/output_dir")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("Kleber/output_dir")
  • Notebooks
  • Google Colab
  • Kaggle
output_dir / runs
93.9 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 9 commits
Kleber's picture
Kleber
Training in progress, step 2000
b605ce5 over 3 years ago
  • Dec17_13-39-19_serv-9213
    Training in progress, step 1000 over 3 years ago
  • Dec17_15-40-32_serv-9213
    Training in progress, step 1000 over 3 years ago
  • Dec17_15-42-08_serv-9213
    End of training over 3 years ago
  • Dec18_04-27-26_serv-9213
    Training in progress, step 2000 over 3 years ago