.. note:: **Here will be soon a detailed description of brevitas export in FINN.**
FINN expects an ONNX model as input. This can be a model trained with `Brevitas <https://github.com/Xilinx/brevitas>`_. Brevitas is a PyTorch library for quantization-aware training and the FINN Docker image comes with several `example Brevitas networks <https://github.com/maltanar/brevitas_cnv_lfc>`_. Brevitas provides an export of a quantized network in ONNX representation. The resulting model consists only of `ONNX standard nodes <https://github.com/onnx/onnx/blob/master/docs/Operators.md>`_, but also contains additional attributes for the ONNX nodes to represent low precision datatypes. To work with the model it is wrapped into :ref:`modelwrapper` provided by FINN.
The model can now be further processed in FINN, the next flow step is :ref:`nw_prep`.
