Instructions to use hf-tiny-model-private/tiny-random-SegformerForSemanticSegmentation 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-SegformerForSemanticSegmentation with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-SegformerForSemanticSegmentation") model = SegformerForSemanticSegmentation.from_pretrained("hf-tiny-model-private/tiny-random-SegformerForSemanticSegmentation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from hf-tiny-model-private/tiny-random-SegformerForSemanticSegmentation: direct link, hf CLI and curl.
- Browser
- Download file 389 Bytes
-
https://huggingface.co/hf-tiny-model-private/tiny-random-SegformerForSemanticSegmentation/resolve/a008f2010856c9c3dd82a080634bcbabfaa04e43/preprocessor_config.json
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-SegformerForSemanticSegmentation@a008f2010856c9c3dd82a080634bcbabfaa04e43/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/hf-tiny-model-private/tiny-random-SegformerForSemanticSegmentation/resolve/a008f2010856c9c3dd82a080634bcbabfaa04e43/preprocessor_config.json
389 Bytes
| { | |
| "crop_size": 64, | |
| "do_normalize": true, | |
| "do_reduce_labels": false, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "image_processor_type": "SegformerImageProcessor", | |
| "image_std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ], | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 64, | |
| "width": 64 | |
| } | |
| } | |