Instructions to use facebook/maskformer-swin-tiny-ade with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/maskformer-swin-tiny-ade with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="facebook/maskformer-swin-tiny-ade")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, MaskFormerForInstanceSegmentation processor = AutoImageProcessor.from_pretrained("facebook/maskformer-swin-tiny-ade") model = MaskFormerForInstanceSegmentation.from_pretrained("facebook/maskformer-swin-tiny-ade", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from facebook/maskformer-swin-tiny-ade: direct link, hf CLI and curl.
- Browser
- Download file 380 Bytes
-
https://huggingface.co/facebook/maskformer-swin-tiny-ade/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://facebook/maskformer-swin-tiny-ade/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/facebook/maskformer-swin-tiny-ade/resolve/main/preprocessor_config.json
380 Bytes
| { | |
| "do_normalize": true, | |
| "do_resize": true, | |
| "feature_extractor_type": "MaskFormerFeatureExtractor", | |
| "ignore_index": 255, | |
| "image_mean": [ | |
| 0.48500001430511475, | |
| 0.4560000002384186, | |
| 0.4059999883174896 | |
| ], | |
| "image_std": [ | |
| 0.2290000021457672, | |
| 0.2239999920129776, | |
| 0.22499999403953552 | |
| ], | |
| "max_size": 2048, | |
| "size": 512, | |
| "size_divisibility": 32 | |
| } | |