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Jason Antic 6 lat temu
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      README.md

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README.md

@@ -87,7 +87,7 @@ Oh and I swear I'll document the code properly...eventually.  Admittedly I'm *on
 
 ### Getting Started Yourself
 This project is built around the wonderful Fast.AI library.  Unfortunately, it's the -old- version and I have yet to upgrade it to the new version.  (That's definitely on the agenda.)  So prereqs, in summary:
-* ***Old* Fast.AI library** **UDATED 11/7/2018** Easiest thing to do in my mind is just to take the fastai/fastai folder and drop it in the root of this project, right next to fasterai's folder. Just today, I found this thread on installing fast.ai 0.7-  This is probably your best resource on this subject!  https://forums.fast.ai/t/fastai-v0-7-install-issues-thread/24652 .  Do this first- this will take you most of the way, including dependencies.
+* ***Old* Fast.AI library** [**UPDATE 11/7/2018**] Easiest thing to do in my mind is just to take the fastai/fastai folder and drop it in the root of this project, right next to fasterai's folder. Just today, I found this thread on installing fast.ai 0.7-  This is probably your best resource on this subject!  https://forums.fast.ai/t/fastai-v0-7-install-issues-thread/24652 .  Do this first- this will take you most of the way, including dependencies.
 * **Pytorch 0.4.1** (needs spectral_norm, so  latest stable release is needed). https://pytorch.org/get-started/locally/
 * **Jupyter Lab** [conda install -c conda-forge jupyterlab]
 * **Tensorboard** (i.e. install Tensorflow) and **TensorboardX** (https://github.com/lanpa/tensorboardX).  I guess you don't *have* to but man, life is so much better with it.  And I've conveniently provided hooks/callbacks to automatically write all kinds of stuff to tensorboard for you already!  The notebooks have examples of these being instantiated (or commented out since I didn't really need the ones doing histograms of the model weights).  Noteably, progress images will be written to Tensorboard every 200 iterations by default, so you get a constant and convenient look at what the model is doing.  [conda install -c anaconda tensorflow-gpu]