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This repository contains 29 complete modules covering everything from fundamental concepts to cutting-edge fine-tuning techniques for Large Language Models. Each module includes detailed Jupyter notebooks with theoretical explanations, practical code examples, and best practices.
End-to-end text summarization project that fine-tunes PEGASUS (`google/pegasus-cnn_dailymail`) on the SAMSum dataset and serves predictions through a FastAPI API.
This paper studies prompt robustness and ambiguity handling for small instruction-tuned LLMs (Qwen2.5-1.5B/3B) in educational tutoring. It evaluates corruption-augmented supervised fine-tuning on GSM8K and DPO in two roles: i augmenting robustness for math reasoning under noisy prompts, ii inducing clarification-seeking behavior on ambiguous prompt