Instructions to use DeepLearner101/ResNetFTFGSM_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeepLearner101/ResNetFTFGSM_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="DeepLearner101/ResNetFTFGSM_2") 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/ResNetFTFGSM_2") model = AutoModelForImageClassification.from_pretrained("DeepLearner101/ResNetFTFGSM_2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a49cab7c8ba6ebba833ba5b8a6a0c54e69b84783f086642170fe64c528e3cd79
- Size of remote file:
- 102 MB
- SHA256:
- 8c28af874ba710478814b16cf4f1b2bea66ec3f097f39d1408e8f5b46e63cc0d
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