diff --git a/transcribe.py b/transcribe.py
index c66bbe61..0b3e4aa7 100755
--- a/transcribe.py
+++ b/transcribe.py
@@ -27,7 +27,8 @@ def fail(message, code=1):
 
 
 def transcribe_file(audio_path, tlog_path):
-    from DeepSpeech import create_model, try_loading  # pylint: disable=cyclic-import,import-outside-toplevel
+    from DeepSpeech import create_model  # pylint: disable=cyclic-import,import-outside-toplevel
+    from util.checkpoints import load_or_init_graph
     initialize_globals()
     scorer = Scorer(FLAGS.lm_alpha, FLAGS.lm_beta, FLAGS.scorer_path, Config.alphabet)
     try:
@@ -47,14 +48,12 @@ def transcribe_file(audio_path, tlog_path):
         logits, _ = create_model(batch_x=batch_x, seq_length=batch_x_len, dropout=no_dropout)
         transposed = tf.nn.softmax(tf.transpose(logits, [1, 0, 2]))
         tf.train.get_or_create_global_step()
-        saver = tf.train.Saver()
         with tf.Session(config=Config.session_config) as session:
-            loaded = try_loading(session, saver, 'best_dev_checkpoint', 'best validation', log_success=False)
-            if not loaded:
-                loaded = try_loading(session, saver, 'checkpoint', 'most recent', log_success=False)
-            if not loaded:
-                fail('Checkpoint directory ({}) does not contain a valid checkpoint state.'
-                     .format(FLAGS.checkpoint_dir))
+            if FLAGS.load == 'auto':
+                method_order = ['best', 'last']
+            else:
+                method_order = [FLAGS.load]
+            load_or_init_graph(session, method_order)
             session.run(iterator.make_initializer(data_set))
             transcripts = []
             while True: