Deploy Ultralytics YOLO models to Replicate with ready-to-use Cog configurations and automated CI/CD workflows.
This repository provides optimized Replicate deployments for YOLO11n, YOLOv8s WorldV2, and YOLOE-11S models with an automated CI/CD workflow.
ultralytics/replicate/
โ
โโโ yolo11n/ # YOLO11n model deployment
โ โโโ cog.yaml # Cog configuration
โ โโโ predict.py # Prediction interface
โ โโโ README.md # Model documentation
โโโ yolov8s-worldv2/ # YOLOv8s WorldV2 model deployment
โ โโโ cog.yaml # Cog configuration
โ โโโ predict.py # Prediction interface
โ โโโ README.md # Model documentation
โโโ yoloe11s/ # YOLOE-11S model deployment
โ โโโ cog.yaml # Cog configuration
โ โโโ predict.py # Prediction interface
โ โโโ README.md # Model documentation
โโโ assets/ # Sample images for workflow smoke tests
โ
โโโ .github/workflows/ # Automated deployment
โ โโโ push.yml # Model deployment workflow
โ โโโ ci.yml # Code quality checks
โ โโโ format.yml # Code formatting
โ
โโโ test_prediction.py # Local YOLO11n testing utility
โโโ requirements.txt # Dependencies
โโโ LICENSE # AGPL-3.0 license
โโโ README.md # This file
Models deploy to the corresponding Replicate endpoints:
# Clone repository
git clone https://github.com/ultralytics/replicate.git
cd replicate
# Deploy YOLO11n
cd yolo11n
python download.py
cog login
cog push r8.im/ultralytics/yolo11n
# Or deploy another configured model
cd ../yolov8s-worldv2
python download.py
cog push r8.im/ultralytics/yolov8s-worldv2
cd ../yoloe11s
python download.py
cog push r8.im/ultralytics/yoloe-11s-
Setup secrets:
- Go to repository Settings โ Secrets โ Actions
- Add
REPLICATE_API_TOKENwith your Replicate API token
-
Deploy:
- Manual: Actions tab โ "Push YOLO to Replicate" โ Run workflow
- Automatic: Push changes to
mainbuilds, tests, and deploys each configured model
Install Cog (Replicate's deployment tool):
sudo curl -o /usr/local/bin/cog -L https://github.com/replicate/cog/releases/latest/download/cog_$(uname -s)_$(uname -m)
sudo chmod +x /usr/local/bin/cogFor local development and testing:
pip install -r requirements.txt| Directory | Replicate model | Predictor | Notes |
|---|---|---|---|
yolo11n/ |
r8.im/ultralytics/yolo11n |
YOLO |
Official YOLO11n object detection model |
yolov8s-worldv2/ |
r8.im/ultralytics/yolov8s-worldv2 |
YOLOWorld |
Open-vocabulary YOLOv8s WorldV2 model |
yoloe11s/ |
r8.im/ultralytics/yoloe-11s |
YOLOE |
YOLOE-11S segmentation model with class prompt support |
Each model directory includes a download.py script used by the deployment workflow before cog build:
python yolo11n/download.py
python yolov8s-worldv2/download.py
python yoloe11s/download.pyTest the model locally before deploying:
# Test YOLO11n
python yolo11n/download.py
python test_prediction.py --model yolo11n --image assets/bus.jpg- ๐๏ธ Optimized: PyTorch model for fast inference
- ๐ค Automated: GitHub Actions for CI/CD
- ๐ฆ Ready-to-use: Pre-configured deployments for multiple YOLO models
- ๐ Scalable: Auto-scaling Replicate infrastructure
- ๐ฏ Focused: One Cog configuration per model
Ultralytics thrives on community collaboration, and we deeply value your contributions! Whether it's reporting bugs, suggesting features, or submitting code changes, your involvement is crucial.
- Reporting Issues: Encounter a bug? Please report it on GitHub Issues.
- Feature Requests: Have an idea for improvement? Share it via GitHub Issues.
- Pull Requests: Want to contribute code? Please read our Contributing Guide first, then submit a Pull Request.
- Feedback: Share your thoughts and experiences by participating in our official Survey.
A heartfelt thank you ๐ goes out to all our contributors! Your efforts help make Ultralytics tools better for everyone.
Ultralytics offers two licensing options to accommodate diverse needs:
- AGPL-3.0 License: Ideal for students, researchers, and enthusiasts passionate about open collaboration and knowledge sharing. This OSI-approved open-source license promotes transparency and community involvement. See the LICENSE file for details.
- Enterprise License: Designed for commercial applications, this license permits the seamless integration of Ultralytics software and AI models into commercial products and services, bypassing the copyleft requirements of AGPL-3.0. For commercial use cases, please inquire about an Ultralytics Enterprise License.
For bug reports or feature suggestions related to this project or other Ultralytics projects, please use GitHub Issues. For general questions, discussions, and community support, join our Discord server!








