Instructions to use ProbeX/Model-J__ResNet__model_idx_0800 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_0800 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_0800") 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_0800") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0800") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
046b36e | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:414f2a400b6817bd221f6814261fa63a240eca583ab7478c06d54cf3569e8a3d
size 5368
|