LLM 101 Workshop

NIT Calicut, Kozhikode, Kerala

Kurian Benoy

Sunday, March 24, 2024

Who am I

Who am I

  • ML Engineer & Team Lead at a Tech Startup at Singapore
  • I’ve worked in Tech since 2018 and has been, ML Engineer & Data scientist for almost 5 years in various companies.
  • Pursuing MTECH in AI & Data science @ IIIT, Kottayam.
  • Completed BTECH in Computer Science @ Govt Model Engineering College, Thrikkakara.
  • Speaker in International conferences like FOSSASIA Summit, Pycon India, Tensorflow Usergroup India summit etc.

Who am I

  • Volunteer @ Swathanthra Malayalam Computing (SMC)
  • I have contributed to Open source projects like Keras, Transformers, fast.ai etc.
  • Creator of Indic Subtitler and Malayalam voice models like Vegam-whisper, MalWhisper etc.
  • Maintains whisper_normalizer a python packages with 100K monthly downloads.

Introduction to LLMs

About cursor

Other cheap or inexpensive tools for Code generation

Let’s build something cool

  • What should be that cool thing?
  • Let’s build a website?
  • You all have seen that website

Let’s build something cool

Landing page of FOSSMEET Website

Demo time


Final Result with be pushed in website


  • Not Open-source AI, but closed-source AI
  • OpenAI will be know for the ChatGPT moment.
  • Yet they were also behind all the work in GPT series, DALL-E, Gym, Gym-Netro, OpenAI Five beat 5 Doto players in 2018 etc
  • Whisper is the most under-rated models released by OpenAI.

OpenAI Demo

Advanced LLMS

  • Advanced techniques
  • RAG
  • Jail breaking
  • Chatgpt + tools

How to fine tune LLM models?

  • You need to fine-tune LLMs for only domain specific models

Slides generated by Nithin by Claude3 Opus Sonnet


    1. Introduction to GPT
    1. How GPT Works
    1. Applications and Use Cases
    1. Future of GPT and AI

Introduction to GPT

  • What is GPT (Generative Pre-trained Transformer)?
  • Key breakthroughs and milestones in language models
  • Importance and impact of GPT on natural language processing

How GPT Works

  • Transformer architecture and self-attention mechanism
  • Pre-training on large text corpora
  • Fine-tuning for specific tasks and applications
  • Key capabilities: text generation, language understanding, question answering

Applications and Use Cases

  • Conversational AI and virtual assistants
  • Content generation (articles, stories, code)
  • Language translation and summarization
  • Question answering and knowledge extraction
  • Potential impact on various industries (education, healthcare, finance, etc.)