Instructions to use hf-tiny-model-private/tiny-random-UperNetForSemanticSegmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-UperNetForSemanticSegmentation with Transformers:
# Load model directly from transformers import AutoImageProcessor, UperNetForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-UperNetForSemanticSegmentation") model = UperNetForSemanticSegmentation.from_pretrained("hf-tiny-model-private/tiny-random-UperNetForSemanticSegmentation") - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
94ce291 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:4e866fc4f9adfd5b769e1905d6e7a75c4889b3ab74d01f0cc710abb6c047ace3
size 86895200
|