Instructions to use ProbeX/Model-J__ResNet__model_idx_0755 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_0755 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_0755") 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_0755") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0755") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6d4bd6fec9c26b145befcf05e8a80bb0605eb177154858d5efb3275492e0f2a0
- Size of remote file:
- 171 MB
- SHA256:
- 04a7563cd61bb3ed98585697419c5ede5b2d4278f101a9975285935c57e6302d
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