diff --git a/README.md b/README.md
index 6ce73bd743804d70f0d2393b490193780123fdce..0af83baad4a87a4613fafb191875de8f98753ead 100644
--- a/README.md
+++ b/README.md
@@ -31,7 +31,24 @@ From a checkout you can run the unit tests with:
 nosetests .
 ```
 
-## Making predictions
+## Making predictions from the command-line
+
+```shell
+$ mhcflurry-predict --alleles HLA-A0201 HLA-A0301 --peptides SIINFEKL SIINFEKD SIINFEKQ
+Predicting for 2 alleles and 3 peptides = 6 predictions
+allele,peptide,mhcflurry_prediction
+HLA-A0201,SIINFEKL,10672.34765625
+HLA-A0201,SIINFEKD,26042.716796875
+HLA-A0201,SIINFEKQ,26375.794921875
+HLA-A0301,SIINFEKL,25532.703125
+HLA-A0301,SIINFEKD,24997.876953125
+HLA-A0301,SIINFEKQ,28262.828125
+```
+
+You can also specify the input and output as CSV files. Run `mhcflurry-predict -h` for details.
+
+
+## Making predictions from Python
 
 ```python
 from mhcflurry import predict
diff --git a/mhcflurry/predict_command.py b/mhcflurry/predict_command.py
index dec8be97fe312e24834fd556fa40eea0794ff0e3..4a010402ecb357d296a574c2c89a93ec116051ad 100644
--- a/mhcflurry/predict_command.py
+++ b/mhcflurry/predict_command.py
@@ -137,7 +137,6 @@ def run(argv=sys.argv[1:]):
 
     predictions = {}  # allele -> peptide -> value
     for (allele, sub_df) in df.groupby(args.allele_column):
-        print(sub_df)
         logging.info("Running %d predictions for allele %s" % (
             len(sub_df), allele))
         model = class1_allele_specific_loader.from_allele_name(allele)