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rchan26
/
dit_base_binary_task

Image Classification
Transformers
PyTorch
beit
Generated from Trainer
Model card Files Files and versions
xet
Community
1

Instructions to use rchan26/dit_base_binary_task with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use rchan26/dit_base_binary_task with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="rchan26/dit_base_binary_task")
    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("rchan26/dit_base_binary_task")
    model = AutoModelForImageClassification.from_pretrained("rchan26/dit_base_binary_task")
  • Notebooks
  • Google Colab
  • Kaggle
dit_base_binary_task
687 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 5 commits
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model
ac52ddb over 2 years ago
  • .gitattributes
    1.48 kB
    initial commit over 3 years ago
  • .gitignore
    13 Bytes
    End of training over 3 years ago
  • README.md
    4.97 kB
    Update README.md over 3 years ago
  • config.json
    1.12 kB
    End of training over 3 years ago
  • model.safetensors
    343 MB
    xet
    Adding `safetensors` variant of this model over 2 years ago
  • preprocessor_config.json
    325 Bytes
    End of training over 3 years ago
  • pytorch_model.bin
    343 MB
    xet
    End of training over 3 years ago
  • training_args.bin
    3.44 kB
    xet
    End of training over 3 years ago