Instructions to use ProbeX/Model-J__ResNet__model_idx_0640 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_0640 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_0640") 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_0640") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0640") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0d021e3cf63e927d1b26eccdd1b134526de922a36a056f9a8639c987789c7424
- Size of remote file:
- 5.37 kB
- SHA256:
- 80b0676b094f521f8f87616c0a2a4390e8f7c130d5090f79b1e87060b26e7a3a
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