Instructions to use ProbeX/Model-J__ResNet__model_idx_0774 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_0774 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_0774") 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_0774") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0774") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 874724de97784ddaae6937f64e40c0fcdae3b3c27f2878a969968ed253d67b1b
- Size of remote file:
- 5.37 kB
- SHA256:
- fb41c033c8b3de4a751badccd2c2f036f47b175b122c2872fd6cbbd3f534e7b5
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