Instructions to use ProbeX/Model-J__ResNet__model_idx_0817 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_0817 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_0817") 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_0817") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0817") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb019c518236bf9db456f8b0fe7e49238da5417ea734e43e9facca6e21d66ba8
- Size of remote file:
- 5.37 kB
- SHA256:
- 99e0af9ef9911a89dc0a50a1fb465ff44ef9d3a530937b197ffca91609c171eb
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