Instructions to use ProbeX/Model-J__DINO__model_idx_0062 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_0062 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_0062") 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_0062") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0062", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0f4b9f543f4c135c250ddbb08f698a355a19c08e356ff1fb014016bf7ccb6c2
- Size of remote file:
- 5.37 kB
- SHA256:
- cf59bc9640341022c3a0a18dbb64b0147cbfe13fce88740548bcce03d56f3fe2
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