Instructions to use ProbeX/Model-J__ResNet__model_idx_0815 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_0815 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_0815") 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_0815") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0815") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ed85b5bdc1650d99b741341b7a44659e2ba1067cfcea90ca7558843ceda36de7
- Size of remote file:
- 5.37 kB
- SHA256:
- aad817b2add32b7fe3b9c4bbb922d91e1406870f961f99394b968512e8c820bc
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