Instructions to use gOLIVES/OLIVES_Dataset_Models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gOLIVES/OLIVES_Dataset_Models with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="gOLIVES/OLIVES_Dataset_Models") 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("gOLIVES/OLIVES_Dataset_Models") model = AutoModelForImageClassification.from_pretrained("gOLIVES/OLIVES_Dataset_Models", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: mit | |
| datasets: | |
| - gOLIVES/OLIVES_Dataset | |
| metrics: | |
| - accuracy | |
| pipeline_tag: image-classification | |
| tags: | |
| - medical | |