Instructions to use mrsarthakgupta/onnx-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrsarthakgupta/onnx-classifier with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("mrsarthakgupta/onnx-classifier") model = AutoModel.from_pretrained("mrsarthakgupta/onnx-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from mrsarthakgupta/onnx-classifier: direct link, hf CLI and curl.
- Browser
- Download file 351 Bytes
-
https://huggingface.co/mrsarthakgupta/onnx-classifier/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://mrsarthakgupta/onnx-classifier/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/mrsarthakgupta/onnx-classifier/resolve/main/preprocessor_config.json
351 Bytes
| { | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.48145466, 0.4578275, 0.40821073 | |
| ], | |
| "image_processor_type": "ViTFeatureExtractor", | |
| "image_std": [ | |
| 0.26862954, 0.26130258, 0.27577711 | |
| ], | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 224, | |
| "width": 224 | |
| } | |
| } |