Instructions to use ProbeX/Model-J__ResNet__model_idx_0807 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_0807 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_0807") 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_0807") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0807") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 47a35b2b67388971d0cde6ff3c1bb4e9edae1036cceba050ab43d58c6c080094
- Size of remote file:
- 171 MB
- SHA256:
- ac8d8dc9c9b3d08804277c856b9ecba704b696c7fdd634156b383100be21895c
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