# 📖 LLM Compatibility Advisor — User Growth & Documentation Plan ## 📖 Overview This document outlines the strategy for expanding the user base of the **LLM Compatibility Advisor**, continuously improving its functionality, and maintaining transparent project documentation for contributors, students, and AI communities. It will also serve as a living changelog and roadmap. --- ## 📅 Weekly/Monthly Actionables - **Week 1-3:** Literature review, finalize objectives, build initial app prototype, deploy to Hugging Face Spaces. - **Week 4-5:** Collect feedback from early users, conduct AI readiness surveys, integrate performance tier adjustments. - **Week 6:** Finalize project documentation, references, publish contribution guide and deployment tutorial. - **Every Month (Post-release):** - Review compatibility tiers against new model releases (Gemma, Mistral, TinyLLaMA variants). - Integrate new quantized model recommendations. - Archive older device datasets and refresh with latest submissions. - Track community feedback and feature requests. --- ## 📢 Outreach Channels - Hugging Face Community Hub - AI Saturdays India and Global Chapters - Student AI club Discord servers - LinkedIn AI student groups - Swecha, PyCon India, and AI open-source events - Open-source AI tool directories (awesome-LLM-tools, AI Community repos) --- ## 📑 Contribution Guide Link **How to contribute:** 👉 https://huggingface.co/spaces/Suryansh14124/LLM-Advisor-ICFAI/wiki/Contributing Includes: - Forking instructions - Branching conventions - Code style guide - Issue reporting protocol - How to add new LLM entries to the compatibility matrix --- ## 🔄 Update Cycle Plan - **LLM Compatibility Matrix:** Review and update every 3 months with latest open-source quantized models and GGUF variants. - **Documentation Updates:** Revise tutorials, contribution guides, and changelogs with each major release. - **Regional Survey Campaigns:** Conduct annual or biannual hardware capability surveys via AI clubs and educational networks. --- > 📌 This document will be updated quarterly alongside model updates and major community onboarding milestones.