Instructions to use facebook/mask2former-swin-base-coco-instance with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mask2former-swin-base-coco-instance with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="facebook/mask2former-swin-base-coco-instance")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, Mask2FormerForUniversalSegmentation processor = AutoImageProcessor.from_pretrained("facebook/mask2former-swin-base-coco-instance") model = Mask2FormerForUniversalSegmentation.from_pretrained("facebook/mask2former-swin-base-coco-instance", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
-
Update preprocessor_config.json (#1)
- Update preprocessor_config.json (100452e767a953b685c859cfa422f6e9e728213f) Co-authored-by: Shivalika Singh <shivi@users.noreply.huggingface.co>e4185db
-
Update preprocessor_config.json
2eab3b4
-
Upload processor
9ba83c4
-
Add model
d7812ef