Instructions to use openmmlab/upernet-convnext-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openmmlab/upernet-convnext-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="openmmlab/upernet-convnext-small")# Load model directly from transformers import AutoImageProcessor, UperNetForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("openmmlab/upernet-convnext-small") model = UperNetForSemanticSegmentation.from_pretrained("openmmlab/upernet-convnext-small") - Inference
- Notebooks
- Google Colab
- Kaggle
what dataset the model is trained on
#2
by Winne - opened
how can i decode the predictions into labels
Refer to the demo notebook: https://huggingface.co/docs/transformers/main/en/model_doc/upernet#resources