diff --git a/flair/models/sequence_tagger_model.py b/flair/models/sequence_tagger_model.py
index 6406b2d80..8059d5b5e 100644
--- a/flair/models/sequence_tagger_model.py
+++ b/flair/models/sequence_tagger_model.py
@@ -11,6 +11,8 @@
 
 from typing import List, Tuple, Union
 
+from flair.training_utils import clear_embeddings
+
 START_TAG: str = '<START>'
 STOP_TAG: str = '<STOP>'
 
@@ -359,6 +361,9 @@ def predict(self, sentences: Union[List[Sentence], Sentence], mini_batch_size=32
         if type(sentences) is Sentence:
             sentences = [sentences]
 
+        # remove previous embeddings
+        clear_embeddings(sentences)
+
         # make mini-batches
         batches = [sentences[x:x + mini_batch_size] for x in range(0, len(sentences), mini_batch_size)]
 
diff --git a/setup.py b/setup.py
index dffec2d5c..a89d4fc79 100644
--- a/setup.py
+++ b/setup.py
@@ -2,7 +2,7 @@
 
 setup(
     name='flair',
-    version='0.2.0',
+    version='0.2.0.post1',
     description='A very simple framework for state-of-the-art NLP',
     long_description=open("README.md").read(),
     long_description_content_type="text/markdown",
diff --git a/tests/test_sequence_tagger.py b/tests/test_sequence_tagger.py
new file mode 100644
index 000000000..dfa8ea736
--- /dev/null
+++ b/tests/test_sequence_tagger.py
@@ -0,0 +1,17 @@
+from flair.data import Sentence
+from flair.models import SequenceTagger
+
+
+def test_tag_sentence():
+
+    # test tagging
+    sentence = Sentence('I love Berlin')
+
+    tagger = SequenceTagger.load('ner')
+
+    tagger.predict(sentence)
+
+    # test re-tagging
+    tagger = SequenceTagger.load('pos')
+
+    tagger.predict(sentence)