Instructions to use ProbeX/Model-J__ResNet__model_idx_0714 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_0714 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_0714") 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_0714") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0714") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 772aed083a29001c897fb8a817ef9f493bdfd2dd09e209c9bcd891c1f6a9e99b
- Size of remote file:
- 5.37 kB
- SHA256:
- fc0b13f1ee25ba8d7d5b99582d907f8b1aeca9b6b42b22a04a9f51c0615ddff1
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