Instructions to use ProbeX/Model-J__ResNet__model_idx_0870 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_0870 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_0870") 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_0870") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0870") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4b145378ef6ac588f0aa2fe59af81c5fff74accdb10158c4ea526652da0a425a
- Size of remote file:
- 5.37 kB
- SHA256:
- c9df781b497094d14aee656b42bf30998b4ddbe1b554e7b6db8857a08b453276
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