diff --git a/README.md b/README.md
index ba43e06..0c2ee21 100644
--- a/README.md
+++ b/README.md
@@ -32,9 +32,11 @@ rc compile
 Then you can run a test with e.g.:
 
 ```
-python RJigsawTools/util/run_lvlv.py  --doOverwrite --nevents 10 --verbosity debug --inputDS /afs/cern.ch/work/r/rsmith/lvlv_datasets/
+python RJigsawTools/util/run_lvlv.py  --doOverwrite --nevents 10 --verbosity debug --inputDS /afs/cern.ch/work/l/larry/public/lvlv_datasets/
 ```
 
+(This points to a public directory so this should run for anyone on afs.)
+
 The inputDS option is smart.  You can give supply a local directory, txt file with a list of grid datasets, or a pattern which matches a grid pattern.  If you use the grid options, obviously you need panda stuff setup, which is setup by the setup script.
 
 PLEASE NOTE : The output will be in
@@ -60,4 +62,4 @@ Once you've run on the grid, download the tree output and the metadata output to
 python mergeOutput.py [path to datasets from grid]
 ```
 
-And it will produce combined files containing the trees. One just needs to weight by the branch normweight. The assignment of dataset types is done in discoverInput.py where tags are added to samples based on their names. Then all of one kind of process are combined.
\ No newline at end of file
+And it will produce combined files containing the trees. One just needs to weight by the branch normweight. The assignment of dataset types is done in discoverInput.py where tags are added to samples based on their names. Then all of one kind of process are combined.