Instructions to use ProbeX/Model-J__ResNet__model_idx_0604 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_0604 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_0604") 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_0604") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0604") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a8609ff3003ac9e812e2bea16e211df29958d08c69815e2006e9abc99c30fdb0
- Size of remote file:
- 5.37 kB
- SHA256:
- 74cbfd849e004703b3572b060712ad041b9fafb8959eeda1f2cf8c5520a49412
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