diff --git a/docs/source/ttnn/ttnn/api.rst b/docs/source/ttnn/ttnn/api.rst
index 420d901d55f..f3c4c3ef2df 100644
--- a/docs/source/ttnn/ttnn/api.rst
+++ b/docs/source/ttnn/ttnn/api.rst
@@ -141,7 +141,6 @@ Pointwise Unary
    ttnn.isneginf
    ttnn.isposinf
    ttnn.leaky_relu
-   ttnn.lerp
    ttnn.lgamma
    ttnn.log
    ttnn.log10
@@ -373,6 +372,7 @@ Pointwise Ternary
    ttnn.addcmul
    ttnn.mac
    ttnn.where
+   ttnn.lerp
    ttnn.addcmul_bw
    ttnn.addcdiv_bw
    ttnn.where_bw
diff --git a/ttnn/cpp/ttnn/operations/eltwise/ternary/ternary_pybind.hpp b/ttnn/cpp/ttnn/operations/eltwise/ternary/ternary_pybind.hpp
index 6b2215f17d3..03efd382b98 100644
--- a/ttnn/cpp/ttnn/operations/eltwise/ternary/ternary_pybind.hpp
+++ b/ttnn/cpp/ttnn/operations/eltwise/ternary/ternary_pybind.hpp
@@ -22,7 +22,7 @@ namespace ternary {
 namespace detail {
 
 template <typename ternary_operation_t>
-void bind_ternary_composite_float(py::module& module, const ternary_operation_t& operation, const std::string& description) {
+void bind_ternary_composite_float(py::module& module, const ternary_operation_t& operation, const std::string& description, const std::string& supported_dtype = "BFLOAT16") {
     auto doc = fmt::format(
         R"doc(
         {2}
@@ -34,21 +34,26 @@ void bind_ternary_composite_float(py::module& module, const ternary_operation_t&
 
 
         Keyword Args:
-            value (float, optional): Float value. Defaults to `1`.
+            value (float, optional): Scalar value to be multiplied.
             memory_config (ttnn.MemoryConfig, optional): Memory configuration for the operation. Defaults to `None`.
 
         Returns:
             ttnn.Tensor: the output tensor.
 
-        Supported dtypes and layouts:
+        Note:
+            Supported dtypes, layouts, and ranks:
 
-            +----------------------------+---------------------------------+-------------------+
-            |     Dtypes                 |         Layouts                 |     Ranks         |
-            +----------------------------+---------------------------------+-------------------+
-            |    BFLOAT16                |          TILE                   |      2, 3, 4      |
-            +----------------------------+---------------------------------+-------------------+
+            .. list-table::
+               :header-rows: 1
 
-            Note : bfloat8_b/bfloat4_b supports only on TILE_LAYOUT
+               * - Dtypes
+                 - Layouts
+                 - Ranks
+               * - {3}
+                 - TILE
+                 - 2, 3, 4
+
+            bfloat8_b/bfloat4_b supports only on TILE_LAYOUT
 
         Example:
             >>> tensor1 = ttnn.to_device(ttnn.from_torch(torch.tensor((1, 2), dtype=torch.bfloat16)), device)
@@ -58,7 +63,8 @@ void bind_ternary_composite_float(py::module& module, const ternary_operation_t&
         )doc",
         operation.base_name(),
         operation.python_fully_qualified_name(),
-        description);
+        description,
+        supported_dtype);
 
     bind_registered_operation(
         module,
@@ -77,7 +83,7 @@ void bind_ternary_composite_float(py::module& module, const ternary_operation_t&
             py::arg("input_tensor_b"),
             py::arg("input_tensor_c"),
             py::kw_only(),
-            py::arg("value") = 1.0f,
+            py::arg("value"),
             py::arg("memory_config") = std::nullopt});
 }
 
@@ -89,7 +95,7 @@ void bind_ternary_where(py::module& module, const ternary_operation_t& operation
 
         Args:
             input_tensor_a (ttnn.Tensor): the input tensor.
-            input_tensor_b (ttnn.Tensor or number): the input tensor.
+            input_tensor_b (ttnn.Tensor or Number): the input tensor.
             input_tensor_c (ttnn.Tensor or Number): the input tensor.
 
 
@@ -99,15 +105,20 @@ void bind_ternary_where(py::module& module, const ternary_operation_t& operation
             queue_id (int, optional): command queue id. Defaults to `0`.
 
 
-        Supported dtypes and layouts:
+        Note:
+            Supported dtypes, layouts, and ranks:
 
-        +----------------------------+---------------------------------+-------------------+
-        |     Dtypes                 |         Layouts                 |     Ranks         |
-        +----------------------------+---------------------------------+-------------------+
-        |    BFLOAT16                |          TILE                   |      2, 3, 4      |
-        +----------------------------+---------------------------------+-------------------+
+            .. list-table::
+               :header-rows: 1
 
-        Note : bfloat8_b/bfloat4_b supports only on TILE_LAYOUT
+               * - Dtypes
+                 - Layouts
+                 - Ranks
+               * - BFLOAT16, BFLOAT8_B
+                 - TILE
+                 - 2, 3, 4
+
+            bfloat8_b/bfloat4_b supports only on TILE_LAYOUT
 
         Example:
 
@@ -267,7 +278,7 @@ void bind_ternary_mac(py::module& module, const ternary_operation_t& operation,
 
         Args:
             input_tensor_a (ttnn.Tensor): the input tensor.
-            input_tensor_b (ttnn.Tensor or number): the input tensor.
+            input_tensor_b (ttnn.Tensor or Number): the input tensor.
             input_tensor_c (ttnn.Tensor or Number): the input tensor.
 
         Keyword Args:
@@ -276,15 +287,20 @@ void bind_ternary_mac(py::module& module, const ternary_operation_t& operation,
         Returns:
             ttnn.Tensor: the output tensor.
 
-        Supported dtypes and layouts:
+        Note:
+            Supported dtypes, layouts, and ranks:
 
-            +----------------------------+---------------------------------+-------------------+
-            |     Dtypes                 |         Layouts                 |     Ranks         |
-            +----------------------------+---------------------------------+-------------------+
-            |    BFLOAT16                |          TILE                   |      2, 3, 4      |
-            +----------------------------+---------------------------------+-------------------+
+            .. list-table::
+               :header-rows: 1
 
-            Note : bfloat8_b/bfloat4_b supports only on TILE_LAYOUT
+               * - Dtypes
+                 - Layouts
+                 - Ranks
+               * - BFLOAT16, BFLOAT8_B
+                 - TILE
+                 - 2, 3, 4
+
+            bfloat8_b/bfloat4_b supports only on TILE_LAYOUT
 
         Example:
             >>> tensor1 = ttnn.to_device(ttnn.from_torch(torch.tensor((1, 2), dtype=torch.bfloat16)), device=device)
@@ -336,28 +352,29 @@ void py_module(py::module& module) {
     detail::bind_ternary_composite_float(
         module,
         ttnn::addcmul,
-        R"doc(compute Addcmul :attr:`input_tensor_a` and :attr:`input_tensor_b` and :attr:`input_tensor_c` and returns the tensor with the same layout as :attr:`input_tensor_a`)doc");
+        R"doc(Computes Addcmul on :attr:`input_tensor_a`, :attr:`input_tensor_b` and :attr:`input_tensor_c` and returns the tensor with the same layout as :attr:`input_tensor_a`)doc",
+        R"doc(BFLOAT16, BFLOAT8_B)doc");
 
     detail::bind_ternary_composite_float(
         module,
         ttnn::addcdiv,
-        R"doc(compute Addcdiv :attr:`input_tensor_a` and :attr:`input_tensor_b` and :attr:`input_tensor_c` and returns the tensor with the same layout as :attr:`input_tensor_a`)doc");
+        R"doc(Computes Addcdiv on :attr:`input_tensor_a`, :attr:`input_tensor_b` and :attr:`input_tensor_c` and returns the tensor with the same layout as :attr:`input_tensor_a`)doc");
 
     detail::bind_ternary_where(
         module,
         ttnn::where,
-        R"doc(compute Addcdiv :attr:`input_tensor_a` and :attr:`input_tensor_b` and :attr:`input_tensor_c` and returns the tensor with the same layout as :attr:`input_tensor_a`)doc");
+        R"doc(Computes Where on :attr:`input_tensor_a`, :attr:`input_tensor_b` and :attr:`input_tensor_c` and returns the tensor with the same layout as :attr:`input_tensor_a`)doc");
 
     detail::bind_ternary_lerp(
         module,
         ttnn::lerp,
-        R"doc(compute Lerp :attr:`input_tensor_a` and :attr:`input_tensor_b` and :attr:`input_tensor_c` and returns the tensor with the same layout as :attr:`input_tensor_a`
+        R"doc(Computes Lerp on :attr:`input_tensor_a`, :attr:`input_tensor_b` and :attr:`input_tensor_c` and returns the tensor with the same layout as :attr:`input_tensor_a`
         .. math:: \mathrm{{input\_tensor\_a}}_i || \mathrm{{input\_tensor\_b}}_i)doc");
 
     detail::bind_ternary_mac(
         module,
         ttnn::mac,
-        R"doc(compute Mac :attr:`input_tensor_a` and :attr:`input_tensor_b` and :attr:`input_tensor_c` and returns the tensor with the same layout as :attr:`input_tensor_a`)doc");
+        R"doc(Computes Mac on :attr:`input_tensor_a`, :attr:`input_tensor_b` and :attr:`input_tensor_c` and returns the tensor with the same layout as :attr:`input_tensor_a`)doc");
 }
 
 }  // namespace ternary