--- a
+++ b/bilstm_crf_ner/test.py
@@ -0,0 +1,53 @@
+""" Command Line Usage
+Args:
+    eval: Evaluate F1 Score and Accuracy on test set
+    pred: Predict sentence.
+    (optional): Sentence to predict on. If none given, predicts on "Peter Johnson lives in Los Angeles"
+
+Example:
+    > python test.py eval pred "Obama is from Hawaii"
+"""
+
+from model.data_utils import CoNLLDataset
+from model.config import Config
+from model.ner_model import NERModel
+from model.ner_learner import NERLearner
+import sys
+
+
+def main():
+    # create instance of config
+    config = Config()
+    if config.use_elmo: config.processing_word = None
+
+    #build model
+    model = NERModel(config)
+
+    learn = NERLearner(config, model)
+    learn.load()
+
+    if len(sys.argv) == 1:
+        print("No arguments given. Running full test")
+        sys.argv.append("eval")
+        # sys.argv.append("pred")
+
+    if sys.argv[1] == "eval":
+        # create datasets
+        test = CoNLLDataset(config.filename_test, config.processing_word,
+                             config.processing_tag, config.max_iter)
+        learn.evaluate(test)
+
+    # if sys.argv[1] == "pred" or sys.argv[2] == "pred":
+    #     try:
+    #         sent = (sys.argv[2] if sys.argv[1] == "pred" else sys.argv[3])
+    #     except IndexError:
+    #         sent = "Peter Johnson lives in Los Angeles."
+
+    #     print("Predicting sentence: ", sent)
+    #     pred = learn.predict(sent)
+    #     print(pred)
+
+
+
+if __name__ == "__main__":
+    main()