Instructions to use valentinafevu/yolos-fashionpedia with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use valentinafevu/yolos-fashionpedia with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="valentinafevu/yolos-fashionpedia")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("valentinafevu/yolos-fashionpedia") model = AutoModelForObjectDetection.from_pretrained("valentinafevu/yolos-fashionpedia") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5676beaa0cc557bfe5344ce7cac938d6729482fa7dc7e0fb13dc98536b4ea4dc
- Size of remote file:
- 123 MB
- SHA256:
- 1b5f4cc272f8f32b2f25b129f9ce7df4756cb030d5fbd234c790b6a9eef962a1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.