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

  • Log In
  • Sign Up

Shubhamai
/
efficientnet-b7

Image Classification
Transformers
JAX
efficientnet
Model card Files Files and versions
xet
Community

Instructions to use Shubhamai/efficientnet-b7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Shubhamai/efficientnet-b7 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="Shubhamai/efficientnet-b7")
    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("Shubhamai/efficientnet-b7")
    model = AutoModelForImageClassification.from_pretrained("Shubhamai/efficientnet-b7")
  • Notebooks
  • Google Colab
  • Kaggle
efficientnet-b7
267 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
Shubhamai's picture
Shubhamai
Create preprocessor_config.json
f190aed about 3 years ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • config.json
    70.2 kB
    Upload FlaxEfficientNetForImageClassification about 3 years ago
  • flax_model.msgpack
    267 MB
    xet
    Upload FlaxEfficientNetForImageClassification about 3 years ago
  • preprocessor_config.json
    494 Bytes
    Create preprocessor_config.json about 3 years ago