Instructions to use ProbeX/Model-J__DINO__model_idx_0499 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_0499 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_0499") 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_0499") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0499") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 290df6a171fa782b565940674ac7ca693b33d5a5cc3f68f447e5ebf105327ebe
- Size of remote file:
- 5.37 kB
- SHA256:
- 4b156f652d8d7720d7cfeaeea9195819069f84e95284d12f02c127b42e91247e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.