Instructions to use ProbeX/Model-J__ResNet__model_idx_0713 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_0713 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_0713") 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_0713") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0713") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7e2a9b4e9ae3e82119c9af0f8139b7ec3f2b7b01cdaa6aa1bdaf35a21ab1c60
- Size of remote file:
- 5.37 kB
- SHA256:
- 004a01cececff49c5a384d8959eb91a5953d48d8ca0941d85e7a876b3e657cd5
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