Instructions to use ProbeX/Model-J__ResNet__model_idx_0535 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_0535 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_0535") 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_0535") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0535") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
f581741 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:29223bc5ac4cd63e7929a0509c45d6230752b31fd776526b9e2aaca04a872e59
size 5368
|