Instructions to use ProbeX/Model-J__ResNet__model_idx_0900 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_0900 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_0900") 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_0900") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0900") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
a4a4184 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:2ea26db70365932a4a3de8acf884527770f8389757ef10051e38d963657ce2ec
size 5368
|