Instructions to use IDKIS/medsiglip-appendicitis-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IDKIS/medsiglip-appendicitis-binary with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("IDKIS/medsiglip-appendicitis-binary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download processor_config.json from IDKIS/medsiglip-appendicitis-binary: direct link, hf CLI and curl.
- Browser
- Download file 483 Bytes
-
https://huggingface.co/IDKIS/medsiglip-appendicitis-binary/resolve/main/processor_config.json
- Command line
-
hf download hf://IDKIS/medsiglip-appendicitis-binary/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/IDKIS/medsiglip-appendicitis-binary/resolve/main/processor_config.json
483 Bytes
| { | |
| "image_processor": { | |
| "do_convert_rgb": true, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "SiglipImageProcessor", | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "resample": 3, | |
| "rescale_factor": 0.00392156862, | |
| "size": { | |
| "height": 448, | |
| "width": 448 | |
| } | |
| }, | |
| "processor_class": "SiglipProcessor" | |
| } | |