Instructions to use hf-internal-testing/tiny-random-MaskFormerForInstanceSegmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MaskFormerForInstanceSegmentation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="hf-internal-testing/tiny-random-MaskFormerForInstanceSegmentation")# Load model directly from transformers import AutoImageProcessor, MaskFormerForInstanceSegmentation processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-MaskFormerForInstanceSegmentation") model = MaskFormerForInstanceSegmentation.from_pretrained("hf-internal-testing/tiny-random-MaskFormerForInstanceSegmentation") - Notebooks
- Google Colab
- Kaggle
File size: 40 Bytes
ed75abb | 1 2 3 | ---
pipeline_tag: image-segmentation
--- |