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:
- 7c4cf5719c40d7e8f0e3b9ff3e68d418262eb4d6113f0504d3fa39d3df4ae012
- Size of remote file:
- 171 MB
- SHA256:
- 930447e4c6467a90a11e8318f636505548aa89c5c4785c079062271a2a66b4c1
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