Instructions to use ProbeX/Model-J__DINO__model_idx_0800 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_0800 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_0800") 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_0800") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0800", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc98dc38050bd0ad6545ba3ba94c66974918fdec99f1690b28bdeca35a1bc80b
- Size of remote file:
- 5.37 kB
- SHA256:
- 126eac5bc4dd9f865c8f6bfd769a9d153aa6ecf55acc86c9cdacbfb4d5deb2a2
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