Instructions to use ProbeX/Model-J__DINO__model_idx_0144 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_0144 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_0144") 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_0144") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0144", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 56d427d71693cc86080178f348cbe68b629d90c8bddafb7cb62c49f7d5ae83be
- Size of remote file:
- 5.37 kB
- SHA256:
- 43e1a7a56665d05e0f3e0fb1ad7c760eb844bf523005768da6b6cb3f8b405154
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