readme

README.md

@@ -112,3 +112,12 @@ To achieve high-fidelity reasoning in a compact 7B parameter footprint, Energy-I
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 The weights for the **Energy-Intelligence** engine are available in the **Files & versions** tab. This model is ready for deployment in RAG pipelines, automated energy reporting dashboards, and real-time anomaly detection systems.
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+## Training Code Repository
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+The complete training pipeline, including data preparation, fine-tuning, and optimization workflows, is available in the following GitHub repository:
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+🔗 https://github.com/Savaliya03/Architecting-an-Energy-Intelligence-LLM-via-PEFT-Optimization
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+This repository provides implementation details of the model architecture, showcasing how Parameter Efficient Fine-Tuning (PEFT) techniques are used to reduce computational cost while maintaining high performance.