AI & LLM Engineer GitHub Profile README Guide

AI & LLM Engineer GitHub Profile Guide: Showcasing RAG, Agents & Fine-Tuning

Direct Answer (TL;DR)

An AI and LLM Engineer GitHub profile should highlight Hugging Face model cards, retrieval-augmented generation (RAG) benchmarks, autonomous agent frameworks (LangGraph, CrewAI), and model evaluation metrics. Feature links to live Hugging Face spaces and Google Colab notebooks alongside your code.

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### 🤖 Featured AI Systems & Model Weights

<table>
  <tr>
    <td width="50%">
      <h4>🧠 Llama-3-FinMed-8B (Domain Adaptation)</h4>
      <p>LoRA fine-tuned on 100K+ peer-reviewed clinical abstracts. Outperforms baseline Llama-3 by 14% on PubMedQA.</p>
      <a href="https://huggingface.co"><img src="https://img.shields.io/badge/🤗_Hugging_Face-Model_Weights-FFD21E?style=flat" /></a>
    </td>
    <td width="50%">
      <h4>⚡ DocuRAG (Agentic Multimodal Pipeline)</h4>
      <p>Sub-50ms hybrid BM25 + dense vector semantic retrieval over 1M+ technical documents using pgvector and Ollama.</p>
      <a href="https://github.com"><img src="https://img.shields.io/badge/GitHub-Source_Code-181717?style=flat&logo=github" /></a>
    </td>
  </tr>
</table>

Frequently Asked Questions

❓ Should I host model weights on GitHub?

Never commit heavy GGUF or safetensors files to git. Host weights on Hugging Face Model Hub and reference them with badges.

AI & LLM Engineer GitHub Profile Guide: Showcasing RAG, Agents & Fine-Tuning

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Frequently Asked Questions

❓ Should I host model weights on GitHub?

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