Make the README for textsum a little clearer

textsum/README.md

@@ -70,9 +70,7 @@ vocabulary size: Most frequent 200k words from dataset's article and summaries.
 
 <b>How To Run</b>
 
-Pre-requesite:
-
-Install TensorFlow and Bazel.
+Prerequisite: install TensorFlow and Bazel.
 
 ```shell
 # cd to your workspace
@@ -83,7 +81,7 @@ Install TensorFlow and Bazel.
 #    If your data files have different names, update the --data_path.
 #    If you don't have data but want to try out the model, copy the toy
 #    data from the textsum/data/data to the data/ directory in the workspace.
-ls -R
+$ ls -R
 .:
 data  textsum  WORKSPACE
 
@@ -97,10 +95,10 @@ data.py  seq2seq_attention_decode.py  seq2seq_attention.py        seq2seq_lib.py
 ./textsum/data:
 data  vocab
 
-bazel build -c opt --config=cuda textsum/...
+$ bazel build -c opt --config=cuda textsum/...
 
 # Run the training.
-bazel-bin/textsum/seq2seq_attention \
+$ bazel-bin/textsum/seq2seq_attention \
     --mode=train \
     --article_key=article \
     --abstract_key=abstract \
@@ -110,7 +108,7 @@ bazel-bin/textsum/seq2seq_attention \
     --train_dir=textsum/log_root/train
 
 # Run the eval. Try to avoid running on the same machine as training.
-bazel-bin/textsum/seq2seq_attention \
+$ bazel-bin/textsum/seq2seq_attention \
     --mode=eval \
     --article_key=article \
     --abstract_key=abstract \
@@ -120,7 +118,7 @@ bazel-bin/textsum/seq2seq_attention \
     --eval_dir=textsum/log_root/eval
 
 # Run the decode. Run it when the most is mostly converged.
-bazel-bin/textsum/seq2seq_attention \
+$ bazel-bin/textsum/seq2seq_attention \
     --mode=decode \
     --article_key=article \
     --abstract_key=abstract \