Instructions to use ProbeX/Model-J__DINO__model_idx_0300 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_0300 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_0300") 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_0300") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0300", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3f2844fb3be10f01181d09e11859c3838c444523b7b90c83996589111a7d665a
- Size of remote file:
- 5.37 kB
- SHA256:
- 93fa4c1030b8e084e9a50f275d5c1177b7184d5c869e264375f7c59bc4adee8c
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