Up-to-date link to PTQ chapter (instead of obsolete POT)

docs/MO_DG/prepare_model/FP16_Compression.md

@@ -3,7 +3,7 @@
 @sphinxdirective
 
 By default, when IR is saved all relevant floating-point weights are compressed to ``FP16`` data type during model conversion.
-It results in creating a "compressed ``FP16`` model", which occupies about half of 
+It results in creating a "compressed ``FP16`` model", which occupies about half of
 the original space in the file system. The compression may introduce a minor drop in accuracy,
 but it is negligible for most models.
 In case if accuracy drop is significant user can disable compression explicitly.
@@ -29,20 +29,20 @@ To disable compression, use the ``compress_to_fp16=False`` option:
           mo --input_model INPUT_MODEL --compress_to_fp16=False
 
 
-For details on how plugins handle compressed ``FP16`` models, see 
+For details on how plugins handle compressed ``FP16`` models, see
 :doc:`Working with devices <openvino_docs_OV_UG_Working_with_devices>`.
 
 .. note::
 
-   ``FP16`` compression is sometimes used as the initial step for ``INT8`` quantization. 
-   Refer to the :doc:`Post-training optimization <pot_introduction>` guide for more 
+   ``FP16`` compression is sometimes used as the initial step for ``INT8`` quantization.
+   Refer to the :doc:`Post-training optimization <ptq_introduction>` guide for more
    information about that.
 
 
 .. note::
 
    Some large models (larger than a few GB) when compressed to ``FP16`` may consume an overly large amount of RAM on the loading
-   phase of the inference. If that is the case for your model, try to convert it without compression: 
+   phase of the inference. If that is the case for your model, try to convert it without compression:
    ``convert_model(INPUT_MODEL, compress_to_fp16=False)`` or ``convert_model(INPUT_MODEL)``
 
 

docs/OV_Converter_UG/prepare_model/FP16_Compression.md

@@ -36,7 +36,7 @@ For details on how plugins handle compressed ``FP16`` models, see
 .. note::
 
    ``FP16`` compression is sometimes used as the initial step for ``INT8`` quantization.
-   Refer to the :doc:`Post-training optimization <pot_introduction>` guide for more
+   Refer to the :doc:`Post-training optimization <ptq_introduction>` guide for more
    information about that.
 
 @endsphinxdirective