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

Update docs metadata (#3781)

Browse source
This commit is contained in:
Glenn Jocher 2023-07-17 12:40:04 +02:00 • committed by GitHub
parent e324af6a12
commit e8030316f6
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
194 changed files with 783 additions and 308 deletions
Download patch file Download diff file Expand all files Collapse all files

6
docs/models/index.md
View file

@ -1,7 +1,7 @@
---
comments: true
description: Learn about the supported models and architectures, such as YOLOv3, YOLOv5, and YOLOv8, and how to contribute your own model to Ultralytics.
keywords: Ultralytics YOLO, YOLOv3, YOLOv4, YOLOv5, YOLOv6, YOLOv7, YOLOv8, SAM, YOLO-NAS, RT-DETR, object detection, instance segmentation, detection transformers, real-time detection, computer vision, CLI, Python
description: Learn about the YOLO family, SAM, MobileSAM, FastSAM, YOLO-NAS, and RT-DETR models supported by Ultralytics, with examples on how to use them via CLI and Python.
keywords: Ultralytics, documentation, YOLO, SAM, MobileSAM, FastSAM, YOLO-NAS, RT-DETR, models, architectures, Python, CLI
---
# Models
@ -45,4 +45,4 @@ model.info() # display model information
model.train(data="coco128.yaml", epochs=100) # train the model
```
For more details on each model, their supported tasks, modes, and performance, please visit their respective documentation pages linked above.
For more details on each model, their supported tasks, modes, and performance, please visit their respective documentation pages linked above.