Enable Intel® Neural Compressor 4-bits weight-only quantization and add related example

[yuwenzho]

Describe your changes

Support 4-bits weight-only quantization with Intel® Neural Compressor and add related example.

As large language models (LLMs) become more prevalent, there is a growing need for new and improved quantization methods that can meet the computational demands of these modern architectures while maintaining the accuracy. Compared to normal quantization like W8A8, weight only quantization (WOQ) is probably a better trade-off to balance the performance and the accuracy.

Two weight only algorithms are provided in this PR. Round-to-nearest (RTN) is the most straightforward way to quantize weight using scale maps. GPTQ algorithm provides more accurate quantization but requires more computational resources.

More detials please refer to this link

Checklist before requesting a review

• Add unit tests for this change.
• Make sure all tests can pass.
• Update documents if necessary.
• Format your code by running pre-commit run --all-files
• Is this a user-facing change? If yes, give a description of this change to be included in the release notes.

(Optional) Issue link

[github-advanced-security]

lintrunner found more than 10 potential problems in the proposed changes. Check the Files changed tab for more details.

[guotuofeng]

/azp run

[azure-pipelines]

Azure Pipelines successfully started running 2 pipeline(s).