Instructions to use DeepLearner101/ResNet50_FGSM_FT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeepLearner101/ResNet50_FGSM_FT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="DeepLearner101/ResNet50_FGSM_FT") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("DeepLearner101/ResNet50_FGSM_FT") model = AutoModelForImageClassification.from_pretrained("DeepLearner101/ResNet50_FGSM_FT") - Notebooks
- Google Colab
- Kaggle
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Parent(s): bf2f4f2
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{"training_loss": [0.045934756269509144, 0.04033770530738614, 0.03842473761601881], "training_accuracy": [70.22727272727273, 72.8409090909091, 75.68181818181819], "validation_accuracy": [65.27272727272727, 69.27272727272727, 70.0], "adversarial_accuracy": [50.17045454545455, 53.86363636363637, 54.65909090909091], "fgsm_loss": [0.11968670040369034, 0.10262668891386552, 0.09400715353814039]}
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