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

IGNF
/
MAESTRO_FLAIR-HUB_base

Image Segmentation
PyTorch
Transformers
pytorch lightning
self-supervised learning
masked autoencoders
remote sensing
earth observation
multimodal
multitemporal
Model card Files Files and versions
xet
Community
2

Instructions to use IGNF/MAESTRO_FLAIR-HUB_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use IGNF/MAESTRO_FLAIR-HUB_base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-segmentation", model="IGNF/MAESTRO_FLAIR-HUB_base")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("IGNF/MAESTRO_FLAIR-HUB_base", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
MAESTRO_FLAIR-HUB_base
382 kB
Ctrl+K
Ctrl+K
  • 4 contributors
History: 11 commits
michavcr's picture
michavcr
Upload train_val_loss_maeflair.png
293ccd9 verified 5 months ago
  • media
    Upload train_val_loss_maeflair.png 5 months ago
  • .gitattributes
    1.58 kB
    Upload Maestro_Overview.png 5 months ago
  • README.md
    10.9 kB
    Update README.md 5 months ago