Instructions to use microsoft/resnet-26 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/resnet-26 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/resnet-26") 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("microsoft/resnet-26") model = AutoModelForImageClassification.from_pretrained("microsoft/resnet-26") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd8a5456a466b10f38f91c444a92c074b6a300e73271df29872498c829174a1f
- Size of remote file:
- 64.2 MB
- SHA256:
- 7b92817c57040ff2a392638304e4165afc1bd07d4adab3d339887cc3c20957f2
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