Outcome Overview
Create a repository of official reference Jupyter notebooks for advanced users:

• Notebooks for InstructLab components in a way that showcases the customization capabilities and integrations. Examples:
  • Document preparation and preprocessing
  • Preprocessing output to DoclingDocument format
  • SDG consuming DoclingDocument format
  • SDG demonstrating subset selection
  • InstructLab Training
  • Evaluations
  • LLMCompressor of InstructLab tuned model
• Notebooks for InstructLab end-to-end flows per use case (e.g., financial documents, catalog of parts, legal documents, etc.)

Success Criteria

Advanced users (such as AI engineers and data scientists) can execute individual InstructLab components and an end-to-end flow using composable notebooks.

An upstream repository is created with reference notebook implementations.

Expected Results (what, how, when){}

What incremental impact do you expect to create toward the company's Strategic Goals by delivering this outcome?  (possible examples:  unblocking sales, shifts in product metrics, etc. provide links to metrics that will be used post-completion for review & pivot decisions). {}For each expected result, list +what you will measure and when you will measure it (ex. provide links to existing information or metrics that will be used post-completion for review and specify when you will review the measurement such as 60 days after the work is complete)

Post Completion Review – Actual Results{}

After completing the work (as determined by the "when" in Expected Results above), list the actual results observed / measured during Post Completion review(s).