Instructions to use ProbeX/Model-J__ResNet__model_idx_0655 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_0655 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_0655") 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_0655") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0655") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 58635be498d7868a00ad1f456b136d0b75b006ba0c7d13fc96632357475bff04
- Size of remote file:
- 5.37 kB
- SHA256:
- 9cde2478d145b2974e8b0c695f42cde8b19b83c4a5bca8e9d3868bfa2c1373fe
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