Instructions to use ProbeX/Model-J__ResNet__model_idx_0706 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_0706 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_0706") 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_0706") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0706") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fa2551e757b8039508fbcbe996b0613d885bf36615afc55b084a2412efadb094
- Size of remote file:
- 5.37 kB
- SHA256:
- 2ac98110e91c0b1a1bff150b31f99dff6e2c3e6abd1aa39d06f1d6fed21cfc48
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