Instructions to use jameslahm/yoloe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use jameslahm/yoloe with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("jameslahm/yoloe") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Add pipeline tag and license
Browse filesThis PR adds the missing `pipeline_tag` and `license` to the model card metadata.
This will improve discoverability and clarity for users.
README.md
CHANGED
|
@@ -1,5 +1,7 @@
|
|
| 1 |
---
|
| 2 |
library_name: ultralytics
|
|
|
|
|
|
|
| 3 |
---
|
| 4 |
|
| 5 |
# [YOLOE: Real-Time Seeing Anything](https://arxiv.org/abs/2503.07465)
|
|
|
|
| 1 |
---
|
| 2 |
library_name: ultralytics
|
| 3 |
+
pipeline_tag: object-detection
|
| 4 |
+
license: mit
|
| 5 |
---
|
| 6 |
|
| 7 |
# [YOLOE: Real-Time Seeing Anything](https://arxiv.org/abs/2503.07465)
|