Instructions to use ProbeX/Model-J__ResNet__model_idx_0411 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_0411 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_0411") 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_0411") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0411") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8079a8a7f54ba2f5ac8a81858fad463ec4faaabb159dcf1088af8305f4ff2834
- Size of remote file:
- 171 MB
- SHA256:
- f0b68d658d370739dcaeda9eb632bec2464082ed38d9ce38ee7b3264cbbeee57
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