Fix broken links from issue #3605 (#3612)

Fixes #3605

## Description
This PR addresses the issue of broken links detected by the
`github-actions` bot. It fixes three incorrect URLs in the
documentation:

- In `CONTRIBUTING.md`, removed an expired Netlify preview example link.
- In `intermediate_source/compiled_autograd_tutorial.rst`, updated the
link to the "Get Started with PyTorch 2.x" page to its new, correct URL.
- In `recipes_source/intel_neural_compressor_for_pytorch.rst`, updated
the link for Intel® Neural Compressor to point to its main GitHub
repository, as the official documentation site is currently inactive
(returns a 404 error).

## Checklist
- [x] The issue that is being fixed is referred in the description (see
above "Fixes #ISSUE_NUMBER")
- [x] Only one issue is addressed in this pull request
- [x] Labels from the issue that this PR is fixing are added to this
pull request
- [x] No unnecessary issues are included into this pull request

---------

Co-authored-by: sekyondaMeta <127536312+sekyondaMeta@users.noreply.github.com>

Author: Flink-ddd

intermediate_source/compiled_autograd_tutorial.rst

@@ -16,7 +16,7 @@ Compiled Autograd: Capturing a larger backward graph for ``torch.compile``
 
        * PyTorch 2.4
        * Complete the `Introduction to torch.compile <https://pytorch.org/tutorials/intermediate/torch_compile_tutorial.html>`_
-       * Read through the TorchDynamo and AOTAutograd sections of `Get Started with PyTorch 2.x <https://pytorch.org/get-started/pytorch-2.0/>`_
+       * Read through the TorchDynamo and AOTAutograd sections of `Get Started with PyTorch 2.x <https://pytorch.org/get-started/pytorch-2-x/>`_
 
 Overview
 --------

recipes_source/intel_neural_compressor_for_pytorch.rst

@@ -17,7 +17,7 @@ Features
 
 - **Accuracy-driven Tuning:** Intel® Neural Compressor supports accuracy-driven automatic tuning process, provides ``autotune`` API for user usage.
 
-- **Kinds of Quantization:** Intel® Neural Compressor supports a variety of quantization methods, including classic INT8 quantization, weight-only quantization and the popular FP8 quantization. Neural compressor also provides the latest research in simulation work, such as MX data type emulation quantization. For more details, please refer to `Supported Matrix <https://github.com/intel/neural-compressor/blob/master/docs/source/3x/PyTorch.md#supported-matrix>`_.
+- **Kinds of Quantization:** Intel® Neural Compressor supports a variety of quantization methods, including classic INT8 quantization, weight-only quantization and the popular FP8 quantization. Neural compressor also provides the latest research in simulation work, such as MX data type emulation quantization. For more details, please refer to `Supported Matrix <https://github.com/intel/neural-compressor/blob/master/docs/source/PyTorch.md#supported-matrix>`_.
 
 Getting Started
 ---------------
@@ -158,4 +158,4 @@ To leverage accuracy-driven automatic tuning, a specified tuning space is necess
 Tutorials
 ---------
 
-More detailed tutorials are available in the official Intel® Neural Compressor `doc <https://intel.github.io/neural-compressor/latest/docs/source/Welcome.html>`_.
+More detailed tutorials are available in the official Intel® Neural Compressor `doc <https://www.intel.com/content/www/us/en/developer/tools/oneapi/neural-compressor.html>`_.