Instructions to use ProbeX/Model-J__ResNet__model_idx_0607 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_0607 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_0607") 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_0607") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0607", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a748a987e86d706cedfbbc4b4c4c2658f6f02e62f88891a036a201c618efeac
- Size of remote file:
- 5.37 kB
- SHA256:
- 5c872f30dadf884838cf4f343bc13168272486d9638531d4815643d1feb01a95
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