Instructions to use ProbeX/Model-J__DINO__model_idx_0693 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_0693 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_0693") 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_0693") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0693", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- db924fa04b891d19442ef53c3b7bd76307c7179c8f1fd1a266710288162082c3
- Size of remote file:
- 343 MB
- SHA256:
- c9df41b1ba33889729d6703ad795ba0abb0093d7e8306a57bfe18372b790b9c6
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