Instructions to use jimjakdiend/IC_CNN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jimjakdiend/IC_CNN with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jimjakdiend/IC_CNN") 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("jimjakdiend/IC_CNN") model = AutoModelForImageClassification.from_pretrained("jimjakdiend/IC_CNN") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7be9933c85404f4fd87822dc53a5c3d3b829bbb8dad16b7956dd54918c95a3bd
- Size of remote file:
- 4.6 kB
- SHA256:
- ca67458fd4aa049cacf1464bd88f770dd60a0a97c332f6418f6b157c0f65b4e6
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