Instructions to use ProbeX/Model-J__ResNet__model_idx_0748 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_0748 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_0748") 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_0748") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0748") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b140da554253e4234308927164129c4dd1ef2d1672710feedc40802fd0e0d0b6
- Size of remote file:
- 5.37 kB
- SHA256:
- df19e1e793eae5dc5fbcff2824adf72e50dd72b8bfed1a9e792cff2e9429f426
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