Instructions to use ProbeX/Model-J__ResNet__model_idx_0658 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_0658 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_0658") 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_0658") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0658") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 54808d6aa10bfff1af88cd84edccbc1ee37276f6bd0f07441347d78e41cdf4a2
- Size of remote file:
- 5.37 kB
- SHA256:
- e4089ab8da1ce1927b6038e59db7d97cd7887ad7144c3d80c64d6ec18225269a
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