Instructions to use ProbeX/Model-J__ResNet__model_idx_0681 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_0681 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_0681") 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_0681") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0681") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ae166ce6756f186d5f5b0551c759cd7874f5979f9306e59654b4e4e0646fed70
- Size of remote file:
- 5.37 kB
- SHA256:
- 495bb63358bac1f4fbf38dee372809d3f666da54e990d2801c06b71eec925c0f
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