A hands-on, community-driven repo for learning LLM Engineering — from beginner fundamentals to advanced techniques. Updated weekly with new implementations, notebooks, and community contributions!.
Whether you're getting started with prompting and RAG or fine-tuning frontier and local models, this repo is meant to be a living, practical reference — built together with the community.
| Folder | Description |
|---|---|
advanced_rag_implementation |
Advanced Retrieval-Augmented Generation techniques and implementations |
finetuning_frontier_model |
Fine-tuning workflows for frontier/hosted LLMs |
finetuning_local_frontier_models |
Fine-tuning workflows for local/open-weight models |
huggingface_genai_usecase_implementations |
GenAI use-case implementations built with Hugging Face tools |
community-contributions |
Contributions from the community — see below to add yours! |
CONTRIBUTORS.md |
List of everyone who has contributed to this repo |
git clone https://github.com/Abhishekravindran/LLM_Engineering_opensource.git
cd LLM_Engineering_opensourceEach folder is self-contained — check for its own notebook/script and any local requirements.txt before running.
We welcome contributions of all levels — bug fixes, new implementations, improved explanations, or entirely new modules.
To add your work to community-contributions:
- Fork this repository.
- In your fork, click Add file → Create new file.
- In the filename box, type:
(Typing
community-contributions/YOUR_NAME/your_file_name.ipynb/auto-creates the folders.) - Paste or upload your code, then Commit changes.
- Go to your fork's main page → Contribute → Open Pull Request → Create Pull Request.
Please add yourself to CONTRIBUTORS.md in the same PR!
- Keep notebooks/scripts runnable — include any special setup steps in a short header comment or markdown cell.
- Prefer clear, minimal examples over large unexplained code dumps.
- If you're extending an existing module (not
community-contributions), open an issue first to discuss the change.
- Add
requirements.txtper module - Add a module on multi-agent orchestration
- Add a module on evaluation & hallucination detection for LLM pipelines
- Add CI to lint/validate notebooks on PR
MIT
If this repo helps you, consider starring it and sharing it with others learning LLM engineering! Do not forget to star as it will help me contribute more to open source community