Instructions to use ProbeX/Model-J__ResNet__model_idx_0680 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_0680 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_0680") 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_0680") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0680") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fb486fdbd61ecae3fb4a866404af6423f11e98f677448d74b5ba537e1f0c9932
- Size of remote file:
- 5.37 kB
- SHA256:
- 5713a27e61a6ee3cc902d91a266ce59dbd3536c0e573c952ac68b5cefda5734c
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