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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): b3d9d70
Add pytorch_model_04.pth and related files
Browse files- pytorch_model_04.pth +3 -0
- training_metrics_04.json +1 -0
pytorch_model_04.pth
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oid sha256:6b1793cd96e5463804fcb7ffc021a6484430645cdfa27f42a7af6891680573e1
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training_metrics_04.json
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