Instructions to use Francesco/resnet26-224-1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Francesco/resnet26-224-1k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Francesco/resnet26-224-1k") 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("Francesco/resnet26-224-1k") model = AutoModelForImageClassification.from_pretrained("Francesco/resnet26-224-1k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7499c8637ee9f574e4c655f6631eb5e12a2b54c5c7f13c569bf9860047220bab
- Size of remote file:
- 64.2 MB
- SHA256:
- 3d6fc6155bf68607bf03ae19cdc1ceb919344b916aa8889a3fcd6d69f8ca9f45
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