Instructions to use ProbeX/Model-J__ResNet__model_idx_0616 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_0616 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_0616") 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_0616") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0616") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 46c3cd3f3000b002823e6b27a54be39124fff1935332b05a6f472d8b1fcec50d
- Size of remote file:
- 5.37 kB
- SHA256:
- 8046b81f3d224d201a23b583f8a2ae0927ebb01077bd8dea4b544ebd37af59d5
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