Instructions to use ProbeX/Model-J__DINO__model_idx_0208 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_0208 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_0208") 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_0208") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0208", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bcf24c1c678998511ca3748816070274c2c8beb21135679d1ba22badef9cbdee
- Size of remote file:
- 5.37 kB
- SHA256:
- 1cfed9fa43cebf5f70a4f1b1ba19cf486fa33a309391ebb0704657138e86b0f7
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