Instructions to use hf-tiny-model-private/tiny-random-MobileNetV2ForSemanticSegmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-MobileNetV2ForSemanticSegmentation with Transformers:
# Load model directly from transformers import AutoImageProcessor, MobileNetV2ForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-MobileNetV2ForSemanticSegmentation") model = MobileNetV2ForSemanticSegmentation.from_pretrained("hf-tiny-model-private/tiny-random-MobileNetV2ForSemanticSegmentation") - Notebooks
- Google Colab
- Kaggle
| { | |
| "crop_size": { | |
| "height": 32, | |
| "width": 32 | |
| }, | |
| "do_center_crop": true, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "MobileNetV2ImageProcessor", | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "shortest_edge": 32 | |
| } | |
| } | |