Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing

  • Log In
  • Sign Up

J-RUM
/
professions

Image Classification
Transformers
PyTorch
TensorBoard
vit
huggingpics
Eval Results (legacy)
Model card Files Files and versions
xet
Metrics Training metrics Community
1

Instructions to use J-RUM/professions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use J-RUM/professions with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="J-RUM/professions")
    pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")
    # Load model directly
    from transformers import AutoImageProcessor, AutoModelForImageClassification
    
    processor = AutoImageProcessor.from_pretrained("J-RUM/professions")
    model = AutoModelForImageClassification.from_pretrained("J-RUM/professions")
  • Notebooks
  • Google Colab
  • Kaggle
professions / images
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
J-RUM's picture
J-RUM
commit files to HF hub
f584d5c over 2 years ago
  • doctor.jpg
    29.8 kB
    xet
    commit files to HF hub over 2 years ago
  • engineer.jpg
    27.1 kB
    xet
    commit files to HF hub over 2 years ago
  • nurse.jpg
    43 kB
    xet
    commit files to HF hub over 2 years ago
  • professor.jpg
    5.69 kB
    xet
    commit files to HF hub over 2 years ago
  • teacher.jpg
    20.1 kB
    xet
    commit files to HF hub over 2 years ago