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
      • Hardware
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

iRaduS
/
whisper-memory-efficient

Transformers
TensorBoard
Safetensors
Romanian
Generated from Trainer
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use iRaduS/whisper-memory-efficient with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use iRaduS/whisper-memory-efficient with Transformers:

    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("iRaduS/whisper-memory-efficient", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
whisper-memory-efficient / runs
24 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
iRaduS's picture
iRaduS
End of training
50f8155 verified 12 months ago
  • Jul21_20-41-03_b4d2077aec1d
    End of training 12 months ago
  • Jul22_06-35-19_93c50ea632d9
    End of training 12 months ago
  • Jul22_07-08-48_8e35002844f3
    End of training 12 months ago