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

fernando232s
/
vit-model1

Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Model card Files Files and versions
xet
Metrics Training metrics Community
2

Instructions to use fernando232s/vit-model1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use fernando232s/vit-model1 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="fernando232s/vit-model1")
    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("fernando232s/vit-model1")
    model = AutoModelForImageClassification.from_pretrained("fernando232s/vit-model1")
  • Notebooks
  • Google Colab
  • Kaggle
vit-model1 / runs
10.1 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
fernando232s's picture
fernando232s
Model save
661af54 over 3 years ago
  • Jan20_22-41-45_e9705dbf317b
    Model save over 3 years ago