HongChuang/ultralytics-ascend
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions 3

PyCharm Code Inspect fixes (#18392)

Browse source 
Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
This commit is contained in:
Glenn Jocher 2024-12-25 16:24:29 +01:00 • committed by GitHub
parent d35860d4a1
commit e5e91967d9
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
31 changed files with 72 additions and 72 deletions
Download patch file Download diff file Expand all files Collapse all files

2
docs/en/integrations/roboflow.md
View file

@ -161,7 +161,7 @@ You are now ready to train YOLO11 on a custom dataset. Follow this [written guid
## Upload Custom YOLO11 Model Weights for Testing and Deployment
Roboflow offers an infinitely scalable API for deployed models and SDKs for use with NVIDIA Jetsons, Luxonis OAKs, Raspberry Pis, GPU-based devices, and more.
Roboflow offers a scalable API for deployed models and SDKs for use with NVIDIA Jetson, Luxonis OAK, Raspberry Pi, GPU-based devices, and more.
You can deploy YOLO11 models by uploading YOLO11 weights to Roboflow. You can do this in a few lines of Python code. Create a new Python file and add the following code: