Instructions to use ProbeX/Model-J__ResNet__model_idx_0645 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_0645 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_0645") 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_0645") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0645") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d64b9e064138b8a6526ff33c6b4e2ce4445d4a7fc7c0fa971d91abb6618473d
- Size of remote file:
- 5.37 kB
- SHA256:
- 9d2d3b564bbd98bf4dc4c8f5065abb91ea29b8713ed2e6d2cadb2fef7fdca79c
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