https://github.com/ultralytics/replicate
Deploy YOLO models to Replicate with ready-to-use Cog configurations and automated CI/CD. Includes optimized deployments for YOLO11, and reference implementations for custom model deployment.
https://github.com/ultralytics/replicate
ai api ci classification-internal deployment detection ml pose-estimation segmentation ultralytics yolo yolo11 yolov5 yolov8
Last synced: about 1 month ago
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Deploy YOLO models to Replicate with ready-to-use Cog configurations and automated CI/CD. Includes optimized deployments for YOLO11, and reference implementations for custom model deployment.
- Host: GitHub
- URL: https://github.com/ultralytics/replicate
- Owner: ultralytics
- License: agpl-3.0
- Created: 2025-08-04T17:20:03.000Z (2 months ago)
- Default Branch: main
- Last Pushed: 2025-08-26T18:51:41.000Z (about 2 months ago)
- Last Synced: 2025-08-27T01:58:09.280Z (about 2 months ago)
- Topics: ai, api, ci, classification-internal, deployment, detection, ml, pose-estimation, segmentation, ultralytics, yolo, yolo11, yolov5, yolov8
- Language: Python
- Homepage: https://replicate.com/ultralytics/yolo11n
- Size: 240 KB
- Stars: 4
- Watchers: 0
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# 🚀 Ultralytics Replicate
Deploy YOLO11n to Replicate at https://replicate.com/ultralytics/yolo11n with ready-to-use Cog configuration and automated CI/CD workflow.
[](https://github.com/ultralytics/replicate/actions/workflows/push.yml)
[](https://github.com/ultralytics/replicate/actions/workflows/format.yml)
[](https://discord.com/invite/ultralytics)
[](https://community.ultralytics.com/)
[](https://reddit.com/r/ultralytics)
## 🗂️ Repository Structure
This repository provides optimized Replicate deployment for the YOLO11n model with automated CI/CD workflow.
```plaintext
ultralytics/replicate/
│
├── yolo11n/ # YOLO11n model deployment
│ ├── cog.yaml # Cog configuration
│ ├── predict.py # Prediction interface
│ └── README.md # Model documentation
│
├── .github/workflows/ # Automated deployment
│ ├── push.yml # Model deployment workflow
│ ├── ci.yml # Code quality checks
│ └── format.yml # Code formatting
│
├── test_prediction.py # Local testing utility
├── requirements.txt # Dependencies
├── LICENSE # AGPL-3.0 license
└── README.md # This file
```
## ⚡ Quick Start
### Deploy YOLO11n Model
Model will deploy to https://replicate.com/ultralytics/yolo11n:
```bash
# Clone repository
git clone https://github.com/ultralytics/replicate.git
cd replicate
# Deploy to Replicate
cd yolo11n
cog login
cog push r8.im/ultralytics/yolo11n
```
### Automated Deployment with GitHub Actions
1. **Setup secrets:**
- Go to repository Settings → Secrets → Actions
- Add `REPLICATE_API_TOKEN` with your [Replicate API token](https://replicate.com/auth/token)
2. **Deploy:**
- **Manual**: Actions tab → "Push YOLO11n to Replicate" → Run workflow
- **Automatic**: Push changes to `main` branch auto-deploys
## 🛠️ Installation
Install Cog (Replicate's deployment tool):
```bash
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/cog
```
For local development and testing:
```bash
pip install -r requirements.txt
```
## 🎯 YOLO11n Model
- **Purpose**: Official YOLO11n object detection
- **Parameters**: 2.6M parameters
- **Classes**: 80 COCO classes
- **Performance**: 39.5 mAP50-95 on COCO dataset
- **Speed**: Optimized for real-time inference
## 🔧 Model Setup
The model will be automatically downloaded by ultralytics when needed:
```python
from ultralytics import YOLO
model = YOLO("yolo11n.pt") # Downloads automatically if not present
```
## 🧪 Local Testing
Test the model locally before deploying:
```bash
# Test YOLO11n
python test_prediction.py --model yolo11n --image test.jpg
```
## 🚀 Features
- **🏎️ Optimized**: PyTorch model for fast inference
- **🤖 Automated**: GitHub Actions for CI/CD
- **📦 Ready-to-use**: Pre-configured YOLO11n deployment
- **📊 Scalable**: Auto-scaling Replicate infrastructure
- **🎯 Simple**: Single model focus
## 💡 Contribute
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](https://github.com/ultralytics/replicate/issues).
- **Feature Requests**: Have an idea for improvement? Share it via [GitHub Issues](https://github.com/ultralytics/replicate/issues).
- **Pull Requests**: Want to contribute code? Please read our [Contributing Guide](https://docs.ultralytics.com/help/contributing/) first, then submit a Pull Request.
- **Feedback**: Share your thoughts and experiences by participating in our official [Survey](https://www.ultralytics.com/survey?utm_source=github&utm_medium=social&utm_campaign=Survey).
A heartfelt thank you 🙏 goes out to all our contributors! Your efforts help make Ultralytics tools better for everyone.
[](https://github.com/ultralytics/ultralytics/graphs/contributors)
## 📄 License
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](https://opensource.org/license/agpl-v3) open-source license promotes transparency and community involvement. See the [LICENSE](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](https://www.ultralytics.com/license).
## 📮 Contact
For bug reports or feature suggestions related to this project or other Ultralytics projects, please use [GitHub Issues](https://github.com/ultralytics/replicate/issues). For general questions, discussions, and community support, join our [Discord](https://discord.com/invite/ultralytics) server!
