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title: README
emoji: 👀
colorFrom: blue
colorTo: blue
sdk: static
pinned: false
license: apache-2.0
---
## About Us
Deci is on a mission to empower AI teams with advanced tools to remove
development barriers and attain production-grade performance and
efficient inference faster.
If you have questions, please feel free to reach out to us on
[Twitter](https://twitter.com/deci_ai), our
[website](https://deci.ai/contact/) or join our Deep
Learning Daily [Discord
community](https://discord.com/invite/p9ecgRhDR8/).
## **[YOLO-NAS](https://github.com/Deci-AI/super-gradients/blob/master/YOLONAS.md):**
Open source Object Detection foundational model generated by Deci's
Neural Architecture Search Technology. YOLO-NAS is a game-changer in the
world of object detection, providing superior real-time object detection
capabilities and production-ready performance.
## **[SuperGradients](https://github.com/Deci-AI/super-gradients):**
An open-source library for training PyTorch-based computer vision
models. Developed by Deci's deep learning experts for the benefit of the
AI community. Use SuperGradients to boost performance with advanced
techniques. Easily train or fine-tune SOTA computer vision models for
all the main tasks with one training library.
## **[DataGradients](https://github.com/Deci-AI/data-gradients):**
DataGradients is an open-source Python-based library specifically
designed for computer vision dataset analysis. It automatically extracts
features from your datasets and combines them all into a single
user-friendly report.
## **[Deci Deep Learning Platform](https://deci.ai/):**
Simplify and accelerate the development of computer vision and NLP and
Generative AI applications with highly accurate and efficient foundation
models and advanced tools to customize, optimize, and deploy them to
production.
Deci is powered by groundbreaking Automated Neural Architecture
Construction (AutoNAC™) technology. Deci's AutoNAC™ engine democratizes
the use of Neural Architecture Search for every organization and helps
teams quickly generate fast, accurate, and efficient deep learning
models. |