Remove examples folder (microsoft#2171)

## Describe your changes

- Remove examples folder.
-  Remove examples related configs.

## Checklist before requesting a review
- [ ] Add unit tests for this change.
- [ ] Make sure all tests can pass.
- [ ] Update documents if necessary.
- [ ] Lint and apply fixes to your code by running `lintrunner -a`
- [ ] Is this a user-facing change? If yes, give a description of this
change to be included in the release notes.

## (Optional) Issue link

Author: xiaoyu-work

.github/copilot-instructions.md

@@ -61,7 +61,6 @@ Always reference these instructions first and fallback to search or bash command
 ### Repository Structure
 - `olive/` -- Main package directory with core functionality
 - `test/` -- Test suite with requirements-test*.txt files
-- `examples/` -- Example scripts and notebooks (35+ model optimization examples)
 - `docs/` -- Documentation
 - `.github/workflows/` -- CI/CD pipelines (lint.yml, codeql.yml)
 - `olive/passes/onnx` -- Directory of ONNX transformations passes
@@ -87,12 +86,6 @@ Always reference these instructions first and fallback to search or bash command
 - Entry point: `olive` command (defined in setup.py console_scripts)
 - Version location: `olive/__init__.py` (__version__)
 
-### Examples and Documentation
-- Getting started notebooks: `examples/getting_started/`
-- Model-specific examples: `examples/{model_name}/` (phi2, mistral, llama, etc.)
-- Quick start example: Qwen/Qwen2.5-0.5B-Instruct optimization
-- Documentation website: https://microsoft.github.io/Olive/
-
 ### Development Workflow
 - Code style: Black formatter with 120 character line limit
 - Linting: Multiple tools via lintrunner (ruff, pylint, editorconfig-checker, etc.)
@@ -111,4 +104,3 @@ When network connectivity is limited:
 - Focus on configuration validation with `--dry_run` mode
 - Test CLI help commands and basic imports
 - Validate linting and code formatting
-- Use local examples in `examples/` directory for reference

.gitignore

@@ -7,8 +7,6 @@ cache/
 olive_tmp_*/
 /olive-venv
 augmented_model.onnx
-examples/**/data
-examples/**/model
 test/**/data
 nc_workspace/
 run_cache/

.pre-commit-config.yaml

@@ -11,7 +11,6 @@ repos:
     rev: v0.3.1
     hooks:
       - id: absolufy-imports
-        exclude: examples/
   - repo: local
     hooks:
       - id: format-json

MANIFEST.in

@@ -1,5 +1,4 @@
 global-exclude *.py[cod]
-recursive-include examples *
 recursive-include docs *
 prune */**/__pycache__
 prune docs/build/**/*

NEWS.md

@@ -1,5 +1,5 @@
 # 📰 News Archive
-- [ Feb 2025 ] [New Notebook available - Finetune and Optimize DeepSeek R1 with Olive 🐋 ](examples/getting_started/olive-deepseek-finetune.ipynb)
+- [ Feb 2025 ] [New Notebook available - Finetune and Optimize DeepSeek R1 with Olive 🐋 ](https://github.com/microsoft/Olive/blob/main/notebooks/olive-deepseek-finetune.ipynb)
 - [ Nov 2024 ] [Democratizing AI Model optimization with the new Olive CLI](https://onnxruntime.ai/blogs/olive-cli)
 - [ Nov 2024 ] [Unlocking NLP Potential: Fine-Tuning with Microsoft Olive (Ignite Pre-Day Lab PRE016)](https://github.com/Azure/Ignite_FineTuning_workshop)
 - [ Nov 2024 ] [Olive supports generating models for MultiLoRA serving on the ONNX Runtime ](https://onnxruntime.ai/blogs/multilora)

README.md

@@ -20,7 +20,7 @@ Here are some recent videos, blog articles and labs that highlight Olive:
 - [ Aug 2025 ] [Olive 0.9.2 is released with new quantization algorithms](https://github.com/microsoft/Olive/releases/tag/v0.9.2)
 - [ May 2025 ] [Olive 0.9.0 is released with support for NPUs](https://github.com/microsoft/Olive/releases/tag/v0.9.0)
 - [ Mar 2025 ] [Olive 0.8.0 is released with new quantization techniques](https://github.com/microsoft/Olive/releases/tag/v0.8.0)
-- [ Feb 2025 ] [New Notebook available - Finetune and Optimize DeepSeek R1 with Olive 🐋 ](examples/getting_started/olive-deepseek-finetune.ipynb)
+- [ Feb 2025 ] [New Notebook available - Finetune and Optimize DeepSeek R1 with Olive 🐋 ](https://github.com/microsoft/Olive/blob/main/notebooks/olive-deepseek-finetune.ipynb)
 - [ Nov 2024 ] [Democratizing AI Model optimization with the new Olive CLI](https://onnxruntime.ai/blogs/olive-cli)
 - [ Nov 2024 ] [Unlocking NLP Potential: Fine-Tuning with Microsoft Olive (Ignite Pre-Day Lab PRE016)](https://github.com/Azure/Ignite_FineTuning_workshop)
 - [ Nov 2024 ] [Olive supports generating models for MultiLoRA serving on the ONNX Runtime ](https://onnxruntime.ai/blogs/multilora)

docs/architecture.md

@@ -363,7 +363,7 @@ Users can build their own workflows using the python api but we also provide a c
 python –m olive.workflows.run --config <json config path>
 ```
 
-Please refer to `examples/bert_ptq_cpu/bert_config.json` for an example.
+Please refer to [olive-recipes](https://github.com/microsoft/olive-recipes) repo for examples.
 
 This tool is also available for use in the python api
 ```python