Instructions to use eyad-ai/SmartChestXRay with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eyad-ai/SmartChestXRay with PEFT:
Task type is invalid.
- Transformers
How to use eyad-ai/SmartChestXRay with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("eyad-ai/SmartChestXRay", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from eyad-ai/SmartChestXRay: direct link, hf CLI and curl.
- Browser
- Download file 442 Bytes
-
https://huggingface.co/eyad-ai/SmartChestXRay/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://eyad-ai/SmartChestXRay/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/eyad-ai/SmartChestXRay/resolve/main/preprocessor_config.json
442 Bytes
| { | |
| "crop_size": { | |
| "height": 518, | |
| "width": 518 | |
| }, | |
| "do_center_crop": true, | |
| "do_convert_rgb": true, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.5307, | |
| 0.5307, | |
| 0.5307 | |
| ], | |
| "image_processor_type": "BitImageProcessor", | |
| "image_std": [ | |
| 0.2583, | |
| 0.2583, | |
| 0.2583 | |
| ], | |
| "resample": 3, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "shortest_edge": 518 | |
| } | |
| } | |