GEN AI use case: dialogue summary. This notebook is extracted from the course Generative AI with Large Language Models. It is used to understand how input text can affect model performance.

Successfully developed a text summarization model using Seq2Seq with attention to condense multi-turn dialogues from the SAMSum dataset into coherent and informative summaries.

Fine-tuning FLAN-T5 with PPO and PEFT to generate less toxic text summaries. This notebook leverages Meta AI's hate speech reward model and utilizes RLHF techniques for improved safety.

This repository explores enhancing dialogue summarization with commonsense knowledge through the SICK framework, evaluating models on dialogue datasets to assess commonsense's impact on summarization quality.

This notebook fine-tunes the FLAN-T5 model for dialogue summarization, comparing full fine-tuning with Parameter-Efficient Fine-Tuning (PEFT). It evaluates performance using ROUGE metrics, demonstrating PEFT's efficiency while achieving competitive results.

Instruction fine tuning BART for Dialogue Summarization | IT4772E | NLP Project 20232

A dataset focused on summarization of dialogs, which represents the rich domain of Twitter customer care conversations.

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

Fine Tuning pegasus and flan-t5 pre-trained language model on dialogsum datasets for conversation summarization to to optimize context window in RAG-LLMs

Dialogue Summarization application hosted using AWS and CICD deployment with docker and FASTAPI. Model card created in HuggingFace and a deployed on HuggingFace Spaces.

[EMNLP 2023] FaMeSumm: Investigating and Improving Faithfulness of Medical Summarization. Support BART, PEGASUS, T5, mT5, BioBART, etc.

Revisiting Cross-Lingual Summarization: A Corpus-based Study and A New Benchmark with Improved Annotation

EMNLP 2022: ClidSum: A Benchmark Dataset for Cross-Lingual Dialogue Summarization

MEDIQA-Chat Shared Tasks @ ACL-ClinicalNLP 2023

Code and dataset for our Bioinformatics 2022 paper: "A Benchmark for Automatic Medical Consultation System: Frameworks, Tasks and Datasets"

Small finetuned LLMs for a diverse set of useful tasks