[DOCS] Fixing code snippet in Weight Compression (openvinotoolkit#24306)

Fixing code snippet for 4-bit compression in `Weight Compression`
article.

docs/articles_en/openvino-workflow/model-optimization-guide/weight-compression.rst

@@ -70,11 +70,21 @@ where INT4 is considered as the primary precision and INT8 is the backup one.
 It usually results in a smaller model size and lower inference latency, although the accuracy
 degradation could be higher, depending on the model.
 
+The code snippet below shows how to do 4-bit quantization of the model weights represented in OpenVINO IR using NNCF:
+
+.. tab-set::
+
+   .. tab-item:: OpenVINO
+      :sync: openvino
+
+      .. doxygensnippet:: docs/optimization_guide/nncf/code/weight_compression_openvino.py
+         :language: python
+         :fragment: [compression_4bit]
+
+
 The table below summarizes the benefits and trade-offs for each compression type in terms of
 memory reduction, speed gain, and accuracy loss.
 
-  .. code-block:: python
-
 .. list-table::
    :widths: 25 20 20 20
    :header-rows: 1