Instructions to use sj21867/ai_art_exp3_efficientnetb3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sj21867/ai_art_exp3_efficientnetb3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sj21867/ai_art_exp3_efficientnetb3") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("sj21867/ai_art_exp3_efficientnetb3") model = AutoModelForImageClassification.from_pretrained("sj21867/ai_art_exp3_efficientnetb3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from sj21867/ai_art_exp3_efficientnetb3: direct link, hf CLI and curl.
- Browser
- Download file 828 Bytes
-
https://huggingface.co/sj21867/ai_art_exp3_efficientnetb3/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://sj21867/ai_art_exp3_efficientnetb3/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/sj21867/ai_art_exp3_efficientnetb3/resolve/main/preprocessor_config.json
828 Bytes
| { | |
| "_valid_processor_keys": [ | |
| "images", | |
| "do_resize", | |
| "size", | |
| "resample", | |
| "do_center_crop", | |
| "crop_size", | |
| "do_rescale", | |
| "rescale_factor", | |
| "rescale_offset", | |
| "do_normalize", | |
| "image_mean", | |
| "image_std", | |
| "include_top", | |
| "return_tensors", | |
| "data_format", | |
| "input_data_format" | |
| ], | |
| "crop_size": { | |
| "height": 289, | |
| "width": 289 | |
| }, | |
| "do_center_crop": false, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "image_processor_type": "EfficientNetImageProcessor", | |
| "image_std": [ | |
| 0.47853944, | |
| 0.4732864, | |
| 0.47434163 | |
| ], | |
| "include_top": true, | |
| "resample": 0, | |
| "rescale_factor": 0.00392156862745098, | |
| "rescale_offset": false, | |
| "size": { | |
| "height": 300, | |
| "width": 300 | |
| } | |
| } | |