Instructions to use SpotLab/MobileViT_DeepLabv3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SpotLab/MobileViT_DeepLabv3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="SpotLab/MobileViT_DeepLabv3")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, MobileViTForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("SpotLab/MobileViT_DeepLabv3") model = MobileViTForSemanticSegmentation.from_pretrained("SpotLab/MobileViT_DeepLabv3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from SpotLab/MobileViT_DeepLabv3: direct link, hf CLI and curl.
- Browser
- Download file 187 Bytes
-
https://huggingface.co/SpotLab/MobileViT_DeepLabv3/resolve/83887ce83ff6fef727b3630a2b0e9daf07dfbfb7/preprocessor_config.json
- Command line
-
hf download hf://SpotLab/MobileViT_DeepLabv3@83887ce83ff6fef727b3630a2b0e9daf07dfbfb7/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/SpotLab/MobileViT_DeepLabv3/resolve/83887ce83ff6fef727b3630a2b0e9daf07dfbfb7/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 | |
| } | |