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

Dijaaa
/
output_dir

Video Classification
Transformers
TensorBoard
Safetensors
videomae
Model card Files Files and versions
xet
Metrics Training metrics Community

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

  • Libraries
  • Transformers

    How to use Dijaaa/output_dir with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("video-classification", model="Dijaaa/output_dir")
    # Load model directly
    from transformers import AutoImageProcessor, AutoModelForVideoClassification
    
    processor = AutoImageProcessor.from_pretrained("Dijaaa/output_dir")
    model = AutoModelForVideoClassification.from_pretrained("Dijaaa/output_dir")
  • Notebooks
  • Google Colab
  • Kaggle
output_dir / runs
13 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
Dijaaa's picture
Dijaaa
Training in progress, epoch 1
713f608 over 2 years ago
  • Nov10_10-50-58_da590239182c
    Training in progress, epoch 1 over 2 years ago
  • Nov12_13-02-27_15af8409e83a
    Training in progress, epoch 1 over 2 years ago