Instructions to use ProbeX/Model-J__ResNet__model_idx_0807 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_0807 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_0807") 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_0807") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0807") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e39e22a4e03bc94c14bf8b5f810b025c743af65923524f51c1c0f5d5ee22c3d5
- Size of remote file:
- 5.37 kB
- SHA256:
- 029180bcc1ddea409e941bb6b84514099d57ac051286223634edb1712d05a1b7
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