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+# FINN
+
+Fast, Scalable Quantized Neural Network Inference on FPGAs
+
+[![Gitter](https://badges.gitter.im/xilinx-finn/community.svg)](https://gitter.im/xilinx-finn/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)
+
+
+## Description
+
+
+FINN is an experimental framework from Xilinx Research Labs to explore deep neural network inference on FPGAs. It specifically targets quantized neural networks, with emphasis on generating dataflow-style architectures customized for each network.
+For more information, please visit the [project page](https://xilinx.github.io/finn/).
+
+A new, more modular version of FINN is currently under development on GitHub, and we welcome contributions from the community!
+Stay tuned for more updates.
+
+## Old version
+
+We previously released an early-stage prototype of a toolflow that took in Caffe-HWGQ binarized network descriptions and produced . You can find it in the [v0.1](https://github.com/Xilinx/finn/tree/v0.1) branch in this repository.
+Please be aware that this version is deprecated and unsupported, and the master branch does not share history with that branch so it should be treated as a separate repository for all purposes.
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-====
-FINN
-====
-
-
-A Framework for Fast, Scalable Quantized Neural Network Inference
-
-
-Description
-===========
-
-A longer description of your project goes here...
-
-
-Note
-====
-
-This project has been set up using PyScaffold 3.2.1. For details and usage
-information on PyScaffold see https://pyscaffold.org/.