.. Copyright 2018 Peter K. G. Williams and collaborators. Licensed under the Creative Commons Attribution-ShareAlike 4.0 International License. .. _download-trained-networks: Download Some Pre-Trained Neural Network Data ============================================= One nice feature of the *neurosynchro* model is that the data files representing a trained neural network are quite compact. Once a network has been trained for your particular problem space, it’s easy and quick to use it. The tutorial sequence starting with :ref:`download-training-set` describes how to obtain a training set and train the neural nets on your own machine. This step is essential in the (quite common) circumstance that you need a network whose parameter ranges are tuned to your particular application. But here, we’ll just download pre-trained neural network files. All you need to do is download and unpack the bzipped *tar* archive `rimphony_powerlaw_s5-5e7_p1.5-7_nndata.tar.bz2 `_, which is archived on `Zenodo `_ under DOI `10.5281/zenodo.1341364 `_. It’s about 160 kiB. This archive contains the data needed to do synchrotron radiative transfer if your particle distribution is a power-law in energy, isotropic in pitch angle, the power-law indices range between 1.5 and 7, and the relevant harmonic numbers are between 5 and 50,000,000. Unpacking this archive will create a directory named ``rimphony_powerlaw_s5-5e7_p1.5-7``. Remaining steps working from the terminal will assume that you’re working from inside this directory, e.g.:: $ cd rimphony_powerlaw_s5-5e7_p1.5-7 **Next**: :ref:`run some test problems! `