Instructions to use Francesco/resnet34-224-1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Francesco/resnet34-224-1k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Francesco/resnet34-224-1k") 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/resnet34-224-1k") model = AutoModelForImageClassification.from_pretrained("Francesco/resnet34-224-1k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 479177755866d3bb2ccc926360233409d64a0337a89a1ad0e698a39c509fc92d
- Size of remote file:
- 87.3 MB
- SHA256:
- 435140cacb5e32eeceb055bb044984a27656c8825d587b41feeb0f1d8353eb3d
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