Add Fara-7b recipes

[apsonawane]

This pull request introduces a complete ONNX Runtime GenAI example for the Fara-7B vision-language model, including documentation, configuration files for model export and optimization (for both CPU and CUDA), a Python inference script, and supporting metadata. The changes enable users to export, optimize, quantize, and run inference with Fara-7B using ONNX Runtime GenAI, supporting both text and image inputs.

Key changes:

1. Documentation and Metadata

• Added a comprehensive README.md describing the Fara-7B ONNX Runtime GenAI pipeline, setup instructions, usage examples, and directory structure.
• Introduced info.yml with metadata such as supported execution providers, devices, and keywords for discoverability.

2. Model Export and Optimization Pipelines

• Added Olive configuration JSONs for CPU/mobile (cpu_and_mobile/embedding.json, cpu_and_mobile/vision.json, cpu_and_mobile/text.json) and CUDA (cuda/embedding.json, cuda/vision.json, cuda/text.json) pipelines, specifying model export, graph surgeries, optimizations, and quantization/precision steps for each sub-model (vision encoder, embedding, text decoder). [1] [2] [3] [4] [5] [6]

3. Inference Script

• Added inference.py, a Python script for running text or multimodal (image+text) inference with ONNX Runtime GenAI, supporting both batch and interactive modes.

4. Project Structure and Ignore Rules

• Updated .gitignore to exclude generated models, cache, Python bytecode, and log files.

These changes together provide an end-to-end workflow for exporting, optimizing, quantizing, and running inference on the Fara-7B model with ONNX Runtime GenAI, making it easy for users to deploy and test the model on both CPU and GPU platforms.

[Copilot]

Pull request overview

This PR adds a new microsoft-Fara-7B/builtin recipe bundle to export/optimize the Fara-7B vision-language model to ONNX (via Olive) and run it with ONNX Runtime GenAI, including CPU and CUDA pipelines.

Changes:

• Added Olive pipeline JSONs for embedding / vision / text sub-model export + optimization for cpu_and_mobile/ and cuda/.
• Added Python orchestration and runtime scripts (optimize.py, inference.py, user_script.py) plus model code under codes/.
• Added supporting metadata/docs (README.md, info.yml) and local ignore rules (.gitignore).

Reviewed changes

Copilot reviewed 14 out of 15 changed files in this pull request and generated 4 comments.

Show a summary per file

File	Description
microsoft-Fara-7B/builtin/user_script.py	Olive callbacks for loading the custom VL model + IO/dummy input definitions for export.
microsoft-Fara-7B/builtin/requirements.txt	Python dependencies to run Olive export/optimization and scripts.
microsoft-Fara-7B/builtin/optimize.py	Runs the three Olive configs and patches/writes GenAI runtime config files.
microsoft-Fara-7B/builtin/info.yml	Minimal metadata for the builtin recipe directory.
microsoft-Fara-7B/builtin/inference.py	Example ONNX Runtime GenAI inference script for text-only and image+text prompts.
microsoft-Fara-7B/builtin/cuda/embedding.json	CUDA Olive pipeline for exporting/optimizing embedding sub-model.
microsoft-Fara-7B/builtin/cuda/text.json	CUDA Olive pipeline for producing INT4 text decoder via ModelBuilder.
microsoft-Fara-7B/builtin/cuda/vision.json	CUDA Olive pipeline for exporting/optimizing vision encoder sub-model.
microsoft-Fara-7B/builtin/cpu_and_mobile/embedding.json	CPU/mobile Olive pipeline for exporting/quantizing embedding sub-model.
microsoft-Fara-7B/builtin/cpu_and_mobile/text.json	CPU/mobile Olive pipeline for producing INT4 text decoder via ModelBuilder.
microsoft-Fara-7B/builtin/cpu_and_mobile/vision.json	CPU/mobile Olive pipeline for exporting/quantizing vision encoder sub-model.
microsoft-Fara-7B/builtin/codes/modeling_qwen2_5_vl.py	Custom Qwen2.5-VL-derived PyTorch modeling code to enable ONNX export.
microsoft-Fara-7B/builtin/codes/init.py	Package marker for codes/.
microsoft-Fara-7B/builtin/README.md	End-to-end instructions and usage examples for export + inference.
microsoft-Fara-7B/builtin/.gitignore	Ignores generated artifacts and caches for the builtin workflow.

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[devang-ml]

Please add LICENSE file.