Instructions to use apple/deeplabv3-mobilevit-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apple/deeplabv3-mobilevit-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="apple/deeplabv3-mobilevit-small")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, MobileViTForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("apple/deeplabv3-mobilevit-small") model = MobileViTForSemanticSegmentation.from_pretrained("apple/deeplabv3-mobilevit-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from apple/deeplabv3-mobilevit-small: direct link, hf CLI and curl.
- Browser
- Download file 187 Bytes
-
https://huggingface.co/apple/deeplabv3-mobilevit-small/resolve/refs%2Fpr%2F2/preprocessor_config.json
- Command line
-
hf download hf://apple/deeplabv3-mobilevit-small@refs/pr/2/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/apple/deeplabv3-mobilevit-small/resolve/refs%2Fpr%2F2/preprocessor_config.json
187 Bytes
| { | |
| "crop_size": 512, | |
| "do_center_crop": true, | |
| "do_flip_channels": true, | |
| "do_resize": true, | |
| "feature_extractor_type": "MobileViTFeatureExtractor", | |
| "resample": 2, | |
| "size": 544 | |
| } | |