Instructions to use ProbeX/Model-J__ResNet__model_idx_0708 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_0708 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_0708") 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_0708") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0708") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c881a516aa4ec148867cb268a4727356628be3acc43a08ecc017f45273d7546
- Size of remote file:
- 5.37 kB
- SHA256:
- ce856e6cfdf63acd04cbcc25f9d5a40b01df324e9590eec182162a92ee7a8ea9
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