Instructions to use ProbeX/Model-J__DINO__model_idx_0978 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_0978 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_0978") 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_0978") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0978", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bac9fa0e9d6528de955878dc804e77cc02bcde3c521c513ac780aac42a1a3e99
- Size of remote file:
- 5.37 kB
- SHA256:
- 56b346393603a778a0a882a89e333a62496bb6ef740616d4af5206ce7b1bc56f
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