diff --git a/tests/prompt_strategies/test_alpacha.py b/tests/prompt_strategies/test_alpacha.py
index ba2098938..882307d69 100644
--- a/tests/prompt_strategies/test_alpacha.py
+++ b/tests/prompt_strategies/test_alpacha.py
@@ -15,7 +15,11 @@ from axolotl.prompters import AlpacaPrompter
 def fixture_alpacha_dataset():
     return Dataset.from_list(
         [
-            {"instruction": "Evaluate this sentence for spelling and grammar mistakes", "input": "He finnished his meal and left the resturant", "output": "He finished his meal and left the restaurant."}
+            {
+                "instruction": "Evaluate this sentence for spelling and grammar mistakes",
+                "input": "He finnished his meal and left the resturant",
+                "output": "He finished his meal and left the restaurant.",
+            }
         ]
     )
 
@@ -46,9 +50,7 @@ class TestAlpacha:
 
     def test_no_double_im_end(self, alpacha_dataset, tokenizer):
         strategy = AlpacaPromptTokenizingStrategy(
-            AlpacaPrompter(
-                prompt_style="chatml"
-            ),
+            AlpacaPrompter(prompt_style="chatml"),
             tokenizer,
             False,  # train_on_inputs
             2048,  # sequence_len
@@ -60,13 +62,93 @@ class TestAlpacha:
 
         input_ids = dataset_wrapper[0]["input_ids"]
 
-        assert input_ids == [1, 32001, 1587, 13, 20548, 336, 349, 396, 13126, 369, 13966, 264, 3638, 28725, 5881, 1360, 395, 396, 2787, 369, 5312, 3629, 2758, 28723, 12018, 264, 2899, 369, 6582, 1999, 2691, 274, 272, 2159, 28723, 32000, 28705, 13, 32001, 2188, 13, 16627, 11931, 456, 12271, 354, 668, 3572, 304, 18756, 3479, 17179, 13, 2428, 854, 28711, 1497, 516, 11314, 304, 1749, 272, 1846, 324, 440, 32000, 28705, 13, 32001, 13892, 13, 650, 5967, 516, 11314, 304, 1749, 272, 9926, 28723, 32000]
-    
+        assert input_ids == [
+            1,
+            32001,
+            1587,
+            13,
+            20548,
+            336,
+            349,
+            396,
+            13126,
+            369,
+            13966,
+            264,
+            3638,
+            28725,
+            5881,
+            1360,
+            395,
+            396,
+            2787,
+            369,
+            5312,
+            3629,
+            2758,
+            28723,
+            12018,
+            264,
+            2899,
+            369,
+            6582,
+            1999,
+            2691,
+            274,
+            272,
+            2159,
+            28723,
+            32000,
+            28705,
+            13,
+            32001,
+            2188,
+            13,
+            16627,
+            11931,
+            456,
+            12271,
+            354,
+            668,
+            3572,
+            304,
+            18756,
+            3479,
+            17179,
+            13,
+            2428,
+            854,
+            28711,
+            1497,
+            516,
+            11314,
+            304,
+            1749,
+            272,
+            1846,
+            324,
+            440,
+            32000,
+            28705,
+            13,
+            32001,
+            13892,
+            13,
+            650,
+            5967,
+            516,
+            11314,
+            304,
+            1749,
+            272,
+            9926,
+            28723,
+            32000,
+        ]
+
     def test_no_train_on_input(self, alpacha_dataset, tokenizer):
         strategy = AlpacaPromptTokenizingStrategy(
-            AlpacaPrompter(
-                prompt_style="chatml"
-            ),
+            AlpacaPrompter(prompt_style="chatml"),
             tokenizer,
             False,  # train_on_inputs
             2048,  # sequence_len
@@ -78,13 +160,93 @@ class TestAlpacha:
 
         labels = dataset_wrapper[0]["labels"]
 
-        assert labels == [-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 650, 5967, 516, 11314, 304, 1749, 272, 9926, 28723, 32000]
+        assert labels == [
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            -100,
+            650,
+            5967,
+            516,
+            11314,
+            304,
+            1749,
+            272,
+            9926,
+            28723,
+            32000,
+        ]
 
     def test_w_train_on_input(self, alpacha_dataset, tokenizer):
         strategy = AlpacaPromptTokenizingStrategy(
-            AlpacaPrompter(
-                prompt_style="chatml"
-            ),
+            AlpacaPrompter(prompt_style="chatml"),
             tokenizer,
             True,  # train_on_inputs
             2048,  # sequence_len
@@ -96,4 +258,86 @@ class TestAlpacha:
 
         labels = dataset_wrapper[0]["labels"]
 
-        assert labels == [1, 32001, 1587, 13, 20548, 336, 349, 396, 13126, 369, 13966, 264, 3638, 28725, 5881, 1360, 395, 396, 2787, 369, 5312, 3629, 2758, 28723, 12018, 264, 2899, 369, 6582, 1999, 2691, 274, 272, 2159, 28723, 32000, 28705, 13, 32001, 2188, 13, 16627, 11931, 456, 12271, 354, 668, 3572, 304, 18756, 3479, 17179, 13, 2428, 854, 28711, 1497, 516, 11314, 304, 1749, 272, 1846, 324, 440, 32000, 28705, 13, 32001, 13892, 13, 650, 5967, 516, 11314, 304, 1749, 272, 9926, 28723, 32000]
\ No newline at end of file
+        assert labels == [
+            1,
+            32001,
+            1587,
+            13,
+            20548,
+            336,
+            349,
+            396,
+            13126,
+            369,
+            13966,
+            264,
+            3638,
+            28725,
+            5881,
+            1360,
+            395,
+            396,
+            2787,
+            369,
+            5312,
+            3629,
+            2758,
+            28723,
+            12018,
+            264,
+            2899,
+            369,
+            6582,
+            1999,
+            2691,
+            274,
+            272,
+            2159,
+            28723,
+            32000,
+            28705,
+            13,
+            32001,
+            2188,
+            13,
+            16627,
+            11931,
+            456,
+            12271,
+            354,
+            668,
+            3572,
+            304,
+            18756,
+            3479,
+            17179,
+            13,
+            2428,
+            854,
+            28711,
+            1497,
+            516,
+            11314,
+            304,
+            1749,
+            272,
+            1846,
+            324,
+            440,
+            32000,
+            28705,
+            13,
+            32001,
+            13892,
+            13,
+            650,
+            5967,
+            516,
+            11314,
+            304,
+            1749,
+            272,
+            9926,
+            28723,
+            32000,
+        ]