Instructions to use ProbeX/Model-J__ResNet__model_idx_0808 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__ResNet__model_idx_0808 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__ResNet__model_idx_0808") 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("ProbeX/Model-J__ResNet__model_idx_0808") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0808") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 30e0237cea9c90b05365f3b2faad068e6bdbfb73d9e96ac3ca09274ce0788d3d
- Size of remote file:
- 5.37 kB
- SHA256:
- a3665a8021384e58592c087f14fe2f803d5b5e69fd98b48777672d36227f3c00
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