Instructions to use ProbeX/Model-J__ResNet__model_idx_0806 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_0806 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_0806") 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_0806") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0806") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 473494b5cfce70601a4cb0963115b754b7b5df0716606b15d331b5f719a33772
- Size of remote file:
- 5.37 kB
- SHA256:
- 816d5b8439e2e2a3b4a3073fb5f8834ee91d413eecf5f00b118ac424d5106812
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