Instructions to use ProbeX/Model-J__ResNet__model_idx_0410 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_0410 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_0410") 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_0410") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0410") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 20cc4cf009a9d6cef516ca7aef1d8c25770f65be803ec28d1fe2980b40f55d94
- Size of remote file:
- 5.37 kB
- SHA256:
- 2f6c1fe22b4303f9bc68c835db3e8f0467a7488cad655bf4652a16be8504a52a
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