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Geekay
/
flower-classifier

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 Geekay/flower-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Geekay/flower-classifier with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="Geekay/flower-classifier")
    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("Geekay/flower-classifier")
    model = AutoModelForImageClassification.from_pretrained("Geekay/flower-classifier")
  • Notebooks
  • Google Colab
  • Kaggle
flower-classifier
687 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model
669db70 about 3 years ago
  • images
    commit files to HF hub about 3 years ago
  • runs
    commit files to HF hub about 3 years ago
  • .gitattributes
    1.64 kB
    commit files to HF hub about 3 years ago
  • README.md
    782 Bytes
    commit files to HF hub about 3 years ago
  • config.json
    765 Bytes
    commit files to HF hub about 3 years ago
  • model.safetensors
    343 MB
    xet
    Adding `safetensors` variant of this model about 3 years ago
  • preprocessor_config.json
    327 Bytes
    commit files to HF hub about 3 years ago
  • pytorch_model.bin
    343 MB
    xet
    commit files to HF hub about 3 years ago