diff --git a/ivy/functional/frontends/torch/tensor.py b/ivy/functional/frontends/torch/tensor.py
index 13a056436f6a7..f784dccd8fd95 100644
--- a/ivy/functional/frontends/torch/tensor.py
+++ b/ivy/functional/frontends/torch/tensor.py
@@ -1893,6 +1893,29 @@ def index_fill(self, dim, index, value):
         arr = torch_frontend.moveaxis(self, 0, dim)
         return arr
 
+    @with_unsupported_dtypes(
+        {
+            "2.0.1 and below": (
+                "bfloat16",
+                "int8",
+                "uint8",
+                "uint32",
+                "uint16",
+                "uint64",
+                "int16",
+                "float16",
+                "complex128",
+                "complex64",
+                "bool",
+            )
+        },
+        "torch",
+    )
+    def unique_consecutive(self, return_inverse, return_counts, dim):
+        return torch_frontend.unique_consecutive(
+            self, return_inverse, return_counts, dim
+        )
+
     @with_unsupported_dtypes(
         {
             "2.0.1 and below": (
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 76053d9758076..2fc81319b5ef7 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
@@ -12816,3 +12816,48 @@ def test_torch_unique(
         frontend=frontend,
         on_device=on_device,
     )
+
+
+# unique_consecutive
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="unique_consecutive",
+    dtype_x_axis=helpers.dtype_values_axis(
+        available_dtypes=helpers.get_dtypes("valid"),
+        min_num_dims=2,
+        min_dim_size=2,
+        force_int_axis=True,
+        valid_axis=True,
+    ),
+    return_inverse=st.booleans(),
+    return_counts=st.booleans(),
+)
+def test_torch_unique_consecutive(
+    dtype_x_axis,
+    return_inverse,
+    return_counts,
+    frontend,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    on_device,
+    backend_fw,
+):
+    input_dtype, x, axis = dtype_x_axis
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtype,
+        backend_to_test=backend_fw,
+        init_all_as_kwargs_np={"data": x[0]},
+        method_input_dtypes=input_dtype,
+        method_all_as_kwargs_np={
+            "return_inverse": return_inverse,
+            "return_counts": return_counts,
+            "dim": axis,
+        },
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        on_device=on_device,
+    )