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

  • Log In
  • Sign Up

MITLL
/
LADI-v2-classifier-large

Image Classification
Transformers
Safetensors
swinv2
LADI
Aerial Imagery
Disaster Response
Emergency Management
Model card Files Files and versions
xet
Community

Instructions to use MITLL/LADI-v2-classifier-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use MITLL/LADI-v2-classifier-large with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="MITLL/LADI-v2-classifier-large")
    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("MITLL/LADI-v2-classifier-large")
    model = AutoModelForImageClassification.from_pretrained("MITLL/LADI-v2-classifier-large")
  • Notebooks
  • Google Colab
  • Kaggle
LADI-v2-classifier-large
781 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 14 commits
jeffliu-LL's picture
jeffliu-LL
Update README.md
8433c45 verified almost 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    5.74 kB
    Update README.md almost 2 years ago
  • config.json
    1.79 kB
    Upload Swinv2ForImageClassification almost 2 years ago
  • model.safetensors
    781 MB
    xet
    Upload Swinv2ForImageClassification almost 2 years ago
  • preprocessor_config.json
    337 Bytes
    Upload processor about 2 years ago