Instructions to use ProbeX/Model-J__DINO__model_idx_0010 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__DINO__model_idx_0010 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__DINO__model_idx_0010") 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__DINO__model_idx_0010") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0010") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 92e2c94916c2d0b7bfd6a15e658a667cb4e45fabcae6c9a85d1ed9722f536555
- Size of remote file:
- 5.37 kB
- SHA256:
- e0933f77d7241761b9bfec8c5ac2f79881bcaadbe8f89ef41aef2d8b3377fa14
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