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