My lab work of “Generative AI with Large Language Models” course offered by DeepLearning.AI and Amazon Web Services on coursera.

This repo contains implementations of fine-tuning LLaMA LLM model using LoRA weights (PEFT) as well as focuses on the Retrieval Augmented Generation (RAG) framework.

A fine-tuned LLM great at answering questions about car repairs and maintenance.

Practical work of my master's thesis

This repository contains a collection of generative AI models and applications designed for various tasks such as text generation, image synthesis, and style transfer. The models leverage cutting-edge architectures like GPT, GANs, and VAEs, enabling users to explore different generative tasks.

Stumble upon a fine tuning that is unfathomable.

PEFT and LoRA to fine-tune large language models for dialogue summarization, reducing computational resources for broader application.

Fine-tuning an LLM to generate musical micro-genres

Unlocking the Power of Generative AI: In-Context Learning, Instruction Fine-Tuning and Reinforcement Learning Fine-Tuning.

Dialogue Summary LLM - FLAN - T5: An implementation of the Flan-t5 LLM to summarize dialogues. Prompt Engineering , Fine tuning with PEFT and fine tuning with RL (PPO) is explored within this project.

Institute Technical Summer Project -23/24

Build a Multi-turn Conversations Chit-Chat Bot

Comparing popular Parameter Efficient Fine-Tuning (PEFT) techniques for Large Language Models

For this project, I fine-tuned two separate models for three tasks: document summarization, dialogue summarization and text classification

This project is an implementation of the paper: Parameter-Efficient Transfer Learning for NLP, Houlsby [Google], ICML 2019.

This repo contains everything about transformers and NLP.

FineTuning LLMs on conversational medical dataset.

practical projects using LLM, VLM and Diffusion models

NTU Deep Learning for Computer Vision 2023 course