https://github.com/Deci-AI/super-gradients

Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.
https://github.com/Deci-AI/super-gradients

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Last synced: 2 months ago
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Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.

• Host: GitHub
• URL: https://github.com/Deci-AI/super-gradients
• Owner: Deci-AI
• License: apache-2.0
• Created: 2021-11-28T07:58:02.000Z (over 2 years ago)
• Default Branch: master
• Last Pushed: 2024-03-21T12:57:12.000Z (2 months ago)
• Last Synced: 2024-03-21T13:57:34.499Z (2 months ago)
• Topics: dependency-graph
• Language: Jupyter Notebook
• Homepage: https://www.supergradients.com
• Size: 357 MB
• Stars: 4,271
• Watchers: 41
• Forks: 467
• Open Issues: 84
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE.YOLONAS-POSE.md
  • Codeowners: .github/CODEOWNERS

Lists

• awesome-production-machine-learning - SuperGradients - AI/super-gradients.svg?style=social) - SuperGradients is an open-source library for training PyTorch-based computer vision models. (Industry Strength CV)
• awesome-stars - Deci-AI/super-gradients - tune SOTA computer vision models with one open source training library. The home of Yolo-NAS. (Jupyter Notebook)
• awesome-yolo - **Yolo-NAS** - AI. They used their proprietary Neural Architecture Search (AutoNAC) to find and optimize a new Deep Learning Architecture Yolo-NAS: number and sizes of the stages, blocks, channels. Using quantization-aware “QSP” and “QCI” modules consisting of QA-RepVGG blocks provide 8-bit quantization and ensuring that model architecture would be compatible with Post-Training Quantization (PTQ) - giving minimal accuracy loss during PTQ. Yolo-NAS also use hybrid quantization method that selectively quantizes specific layers to optimize accuracy and latency tradeoffs as well as the attention mechanism and inference time reparametrization to enhance detection capabilities. Pre-trained weights are available for research use (non-commercial) on SuperGradients, Deci’s PyTorch-based, open-source CV library. (Uncategorized / Uncategorized)
• awesome-stars - Deci-AI/super-gradients - Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS. (Jupyter Notebook)
• awesome-yolo-object-detection - YOLO-NAS - AI/super-gradients?style=social"/> : Easily train or fine-tune SOTA computer vision models with one open source training library. The home of [Yolo-NAS](https://github.com/Deci-AI/super-gradients/blob/master/YOLONAS.md). [www.supergradients.com](https://www.supergradients.com/). YOLO-NAS: A Next-Generation, Object Detection Foundational Model generated by Deci’s Neural Architecture Search Technology. Deci is thrilled to announce the release of a new object detection model, YOLO-NAS - a game-changer in the world of object detection, providing superior real-time object detection capabilities and production-ready performance. Deci's mission is to provide AI teams with tools to remove development barriers and attain efficient inference performance more quickly. The new YOLO-NAS delivers state-of-the-art (SOTA) performance with the unparalleled accuracy-speed performance, outperforming other models such as YOLOv5, YOLOv6, YOLOv7 and YOLOv8. (Summary)
• awesome-stars - super-gradients - tune SOTA computer vision models with one open source training library. The home of Yolo-NAS. | Deci-AI | 4102 | (Jupyter Notebook)
• awesome-stars - Deci-AI/super-gradients - Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS. (Jupyter Notebook)
• AiTreasureBox - Deci-AI/super-gradients - 06-02_4379_0](https://img.shields.io/github/stars/Deci-AI/super-gradients.svg) |Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.| (Repos)