Instructions to use ProbeX/Model-J__DINO__model_idx_0230 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_0230 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_0230") 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_0230") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0230", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 356be5dc42b6cb3b091f79dda16f8a59a5cbbd0d9b06aa6c88be03b6a73a9d31
- Size of remote file:
- 5.37 kB
- SHA256:
- 6d5b9c5369a4c49f7b8c6cd09bfc88aeff809e2db38fc651d3c241f3495adaa1
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