Instructions to use DeepLearner101/ResNet50_FGSM_FT_Epochs25_Eps015 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeepLearner101/ResNet50_FGSM_FT_Epochs25_Eps015 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="DeepLearner101/ResNet50_FGSM_FT_Epochs25_Eps015") 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_Epochs25_Eps015") model = AutoModelForImageClassification.from_pretrained("DeepLearner101/ResNet50_FGSM_FT_Epochs25_Eps015") - Notebooks
- Google Colab
- Kaggle
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Parent(s): 5f4bbb5
Upload best_hyperparameters.json
Browse filesBest hyperparameters added from previous run.
best_hyperparameters.json
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{"lr": 0.00042840029987674996, "momentum": 0.899203238087435, "weight_decay": 2.830545737226652e-05, "epochs": 10, "epsilon_range": [0.001, 0.25, 0.005]}
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