Added more documentation

README.md

@@ -33,7 +33,7 @@ Under the hood, Equilid uses a neural seq2seq model.  It depends on three librar
 
 Equilid may work with later versions of tensorflow but this hasn't been tested (yet).
 
-Equilid can be installed via pip ``pip install equilid``.  However, this installs only the software and not the trained model.  The trained model downloaded here [http://cs.stanford.edu/~jurgens/models/70lang.tar.gz] (559MB)
+Equilid can be installed via pip ``pip install equilid``.  However, this installs only the software and not the trained model.  The trained model downloaded here [http://cs.stanford.edu/~jurgens/data/70lang.tar.gz] (559MB unarchived).
 
 
 # Usage
@@ -100,8 +100,9 @@ Equilid's training data was drawn from multiple sources:
 
 Changelog
 ---------
-v1.0.1:
+* v1.0.1:
   * Fixed unicode issue
   * Added model download code (untested)
-v1.0: 
+
+* v1.0: 
   * Initial relea

equilid/equilid.py

@@ -259,6 +259,10 @@ def create_model(session, forward_only):
             print("Created model with fresh parameters.")
             session.run(tf.initialize_all_variables())
     else:
+        if not tf.gfile.Exists(FLAGS.model_dir):
+            print("No model file at %s .  Did you download a model yet?" \
+                      % FLAGS.model_dir)
+            sys.exit(1)
         print("loading model from %s" % (FLAGS.model_dir))
         ckpt = tf.train.get_checkpoint_state(FLAGS.model_dir)
         model.saver.restore(session, ckpt.model_checkpoint_path)

setup.py

@@ -3,7 +3,7 @@
 from distutils.core import setup
 
 setup(name='Equilid',
-      version='1.0.0',
+      version='1.0.1',
       description='Socially-Eqiutable Language Identification',
       author='David Jurgens and Yulia Tsvetkov',
       author_email='[email protected]',