Instructions to use Luwayy/disaster_images_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Luwayy/disaster_images_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Luwayy/disaster_images_model") 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("Luwayy/disaster_images_model") model = AutoModelForImageClassification.from_pretrained("Luwayy/disaster_images_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from Luwayy/disaster_images_model: direct link, hf CLI and curl.
- Browser
- Download file 787 Bytes
-
https://huggingface.co/Luwayy/disaster_images_model/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://Luwayy/disaster_images_model/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/Luwayy/disaster_images_model/resolve/main/preprocessor_config.json
787 Bytes
| { | |
| "do_normalize": true, | |
| "do_resize": true, | |
| "image_mean": [0.5, 0.5, 0.5], | |
| "image_processor_type": "ViTImageProcessor", | |
| "image_std": [0.5, 0.5, 0.5], | |
| "size": { | |
| "height": 224, | |
| "width": 224 | |
| }, | |
| "image_formats": [".png", ".jpg", ".jpeg", ".bmp", ".gif", ".tiff"], | |
| "do_verify_images": true, | |
| "exclude_labels": ["Land_Slide"], | |
| "resample_method": "bilinear", | |
| "training_args": { | |
| "batch_size": 16, | |
| "num_epochs": 3, | |
| "learning_rate": 3e-5, | |
| "weight_decay": 0.01, | |
| "evaluation_strategy": "epoch", | |
| "save_strategy": "epoch" | |
| }, | |
| "dataset_split": { | |
| "train_test_ratio": 0.8 | |
| }, | |
| "image_augmentation": { | |
| "resize": [224, 224], | |
| "to_tensor": true, | |
| "normalize": { | |
| "mean": [0.5, 0.5, 0.5], | |
| "std": [0.5, 0.5, 0.5] | |
| } | |
| } | |
| } | |