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

  • Log In
  • Sign Up

openmmlab
/
upernet-convnext-tiny

Image Segmentation
Transformers
PyTorch
Safetensors
English
upernet
vision
Model card Files Files and versions
xet
Community
1

Instructions to use openmmlab/upernet-convnext-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use openmmlab/upernet-convnext-tiny with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-segmentation", model="openmmlab/upernet-convnext-tiny")
    # Load model directly
    from transformers import AutoImageProcessor, UperNetForSemanticSegmentation
    
    processor = AutoImageProcessor.from_pretrained("openmmlab/upernet-convnext-tiny")
    model = UperNetForSemanticSegmentation.from_pretrained("openmmlab/upernet-convnext-tiny")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
upernet-convnext-tiny
482 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 5 commits
nielsr's picture
nielsr HF Staff
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model (#1)
876ffc5 about 3 years ago
  • .gitattributes
    1.48 kB
    initial commit over 3 years ago
  • README.md
    1.55 kB
    Upload README.md with huggingface_hub over 3 years ago
  • config.json
    8.76 kB
    Upload UperNetForSemanticSegmentation over 3 years ago
  • model.safetensors
    241 MB
    xet
    Adding `safetensors` variant of this model (#1) about 3 years ago
  • preprocessor_config.json
    372 Bytes
    Upload processor over 3 years ago
  • pytorch_model.bin
    241 MB
    xet
    Upload UperNetForSemanticSegmentation over 3 years ago