Instructions to use jimjakdiend/CNN_Mult with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jimjakdiend/CNN_Mult with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jimjakdiend/CNN_Mult") 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/CNN_Mult") model = AutoModelForImageClassification.from_pretrained("jimjakdiend/CNN_Mult") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 48ebc6822eb9bc7bdd400dfd4ca8ba8d5403902260a3909928dff943d65080b3
- Size of remote file:
- 4.66 kB
- SHA256:
- f37e224380b13aaf727e8fa4a4cd0d4baa0b5559a28158448a9ad4e321563eb5
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