diff --git a/README.md b/README.md
index d2787f5..b9db6c8 100644
--- a/README.md
+++ b/README.md
@@ -3,7 +3,7 @@ This repo trains and analyzes neural nets for predicting how a tokamak (fusion r
 Generate an h5 file with [data-fetching repo](https://github.com/PlasmaControl/data-fetching)
 
 -------- TO TRAIN A MODEL ---------
-In configs/default.cfg point raw_data_filename to the generated h5 file. Then change preprocessed_data_filename_base to a "base" name for writing processed data. Run preprocess_data.py, which will generate the basename with _train.pkl, _val.pkl, and _test.pkl appended. Change output_dir in the config file to where you want to dump a model, then run python ian_train.py to train a model to go there. To train a full ensemble of models (submitting them to slurm on traverse) do python launch_ensemble.py which will train 10 with 0,...,9 appended to the end. Use modelStats.py {config_filename} to plot training losses.
+In configs/default.cfg point raw_data_filename to the generated h5 file. Then change preprocessed_data_filename_base to a "base" name for writing processed data. Run preprocess_data.py, which will generate the basename with _train.pkl, _val.pkl, and _test.pkl appended. Change output_dir in the config file to where you want to dump a model, then run python ian_train.py to train a model to go there. To train a full ensemble of models (submitting them to slurm on stellar) do python launch_ensemble.py which will train 10 with 0,...,9 appended to the end. Use modelStats.py {config_filename} to plot training losses.
 
 -------- TO CREATE AND VISUALIZE MODEL OUTPUTS ---------
 Run SimpleModelRollout.py {config_filename} (where config_filename is the full path to the config file corresponding to the model) to create a pickle file with the predicted profiles. Set plot_ensemble to True or False depending on whether you're doing ensemble modeling or one model at a time. To visualize the predictions, use prediction_plotter.ipynb
@@ -33,4 +33,4 @@ For pytorch environment setup on PPPL/Princeton's Traverse cluster along with a
     conda install -c anaconda h5py
     conda activate torch
 
-And of course reload anaconda and activate this environment every time you go to run the code.
\ No newline at end of file
+And of course reload anaconda and activate this environment every time you go to run the code.