diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
index 2fc2e29088e22..2cf190bd2ac3d 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
@@ -335,26 +335,16 @@ def _masked_fill_helper(draw):
 @st.composite
 def _repeat_helper(draw):
     shape = draw(
-        helpers.get_shape(
-            min_num_dims=1, max_num_dims=5, min_dim_size=2, max_dim_size=10
-        )
-    )
-
-    input_dtype, x = draw(
-        helpers.dtype_and_values(
-            available_dtypes=helpers.get_dtypes("valid"),
-            shape=shape,
-        )
+        st.shared(helpers.get_shape(min_dim_size=0, max_num_dims=8), key="value_shape")
     )
-
     repeats = draw(
         st.lists(
-            st.integers(min_value=1, max_value=5),
+            st.integers(min_value=0, max_value=5),
             min_size=len(shape),
-            max_size=5,
+            max_size=8,
         )
     )
-    return input_dtype, x, repeats
+    return repeats
 
 
 @st.composite
@@ -11330,11 +11320,18 @@ def test_torch_remainder_(
     class_tree=CLASS_TREE,
     init_tree="torch.tensor",
     method_name="repeat",
-    dtype_x_repeats=_repeat_helper(),
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("valid"),
+        shape=st.shared(
+            helpers.get_shape(min_dim_size=0, max_num_dims=8), key="value_shape"
+        ),
+    ),
+    repeats=_repeat_helper(),
     unpack_repeats=st.booleans(),
 )
 def test_torch_repeat(
-    dtype_x_repeats,
+    dtype_and_x,
+    repeats,
     unpack_repeats,
     frontend_method_data,
     init_flags,
@@ -11343,8 +11340,8 @@ def test_torch_repeat(
     on_device,
     backend_fw,
 ):
-    input_dtype, x, repeats = dtype_x_repeats
-    if unpack_repeats:
+    input_dtype, x = dtype_and_x
+    if unpack_repeats and len(repeats) > 0:
         method_flags.num_positional_args = len(repeats)
         method_kwargs = {f"x{i}": x_ for i, x_ in enumerate(repeats)}
     else: