Instructions to use optimum/deeplabv3-mobilevit-small-neuronx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use optimum/deeplabv3-mobilevit-small-neuronx with Transformers:
# Load model directly from transformers import AutoImageProcessor, MobileViTForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("optimum/deeplabv3-mobilevit-small-neuronx") model = MobileViTForSemanticSegmentation.from_pretrained("optimum/deeplabv3-mobilevit-small-neuronx", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from optimum/deeplabv3-mobilevit-small-neuronx: direct link, hf CLI and curl.
- Browser
- Download file 637 Bytes
-
https://huggingface.co/optimum/deeplabv3-mobilevit-small-neuronx/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://optimum/deeplabv3-mobilevit-small-neuronx/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/optimum/deeplabv3-mobilevit-small-neuronx/resolve/main/preprocessor_config.json
637 Bytes
| { | |
| "_valid_processor_keys": [ | |
| "images", | |
| "segmentation_maps", | |
| "do_resize", | |
| "size", | |
| "resample", | |
| "do_rescale", | |
| "rescale_factor", | |
| "do_center_crop", | |
| "crop_size", | |
| "do_flip_channel_order", | |
| "return_tensors", | |
| "data_format", | |
| "input_data_format" | |
| ], | |
| "crop_size": { | |
| "height": 512, | |
| "width": 512 | |
| }, | |
| "do_center_crop": true, | |
| "do_flip_channel_order": true, | |
| "do_flip_channels": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_processor_type": "MobileViTFeatureExtractor", | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "shortest_edge": 544 | |
| } | |
| } | |