Instructions to use ProbeX/Model-J__DINO__model_idx_0721 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_0721 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_0721") 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_0721") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0721", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e7c60ff5c50de9a4d067c52b31ef7f40e8f6da184807f32d16a8bd1df7986ddd
- Size of remote file:
- 5.37 kB
- SHA256:
- b1758cb4031e60db8989fbdf2d58b43721d8039db621ef6a0fd9e13c250adf89
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.