Who I am, why I write, and why you might be interested — First of all — thank you so much for reading this post! While I’ve been writing on Medium for a couple of years now, I haven’t yet gotten to introducing myself on Medium. I’m a data scientist but my journey has not been typical. I started off getting my PhD…

Organizations are in a race to adopt Large Language Models. Let’s dive into how you can build industry-specific LLMs Through RAG — Companies stand to gain a lot of productivity improvements through LLMs like ChatGPT. But try asking ChatGPT “what is the current inflation in the U.S.” and it gives: I apologize for the confusion, but as an AI language model, I don’t have real-time data or browsing capabilities. My responses are…

A tutorial on fine-tuning the Hugging Face RoBERTa QA Model on custom data and obtaining significant performance boosts — Question Answering and Transformers BERT is a transformer model that took the world by storm in 2019. BERT was trained on unlabeled data by masking words and training the model to predict these masked words based on context. BERT was later fine-tuned on multiple tasks and achieved state of the art performance on many…

Retrieval Augmented Generation (RAG) offers a pathway to integrate large language models like ChatGPT/GPT-4 with custom data, but has limitations. Let’s learn how recent RAG research innovations can solve some of these. — Large language models (LLMs) are all set to revolutionize the financial sector. One use-case are LLMs to pore over troves of documents and find trends in a fraction of time and at a fraction of the cost of analysts. But here’s the catch — the answers you get are only…

Let’s face it — vanilla RAG is pretty dumb. There’s no guarantee responses returned are relevant. Learn how Self-RAG can significantly help — Large language models (LLMs) are all set to revolutionize various industries. Let’s take the example of the financial sector, wherein LLMs can be used to pore over troves of documents and find trends in a fraction of time and at a fraction of the cost of analysts doing the same…

In our experience, within 5–10 minutes, potential clients mention privacy as a big concern for OpenAI based apps. Is there any hope for privately hosted LLMs? — Generative AI is taking industries by storm. Right now, the most attractive markets are saving precious human and monetary resources, using LLMs. These include replacing analysts poring through news articles or documents, revamping legacy chat systems and interactive voice response (IVR) systems, etc. …

Learn how recent advances make it possible to deploy and fine-tune LLMs with Billions of parameters on consumer hardware — even on your own personal laptop! — Large Language Models (LLMs) are taking the world by storm — with the recent developments in ChatGPT/GPT-4 as well as recent open-source models like Llama2. However, these models are extremely memory intensive. Let’s calculate how much memory is needed for putting a 10 Billion parameter in memory. If each parameter…

LLMs are fundamentally changing the way practitioners evaluate performance . Let’s look at the recent progress towards evaluating LLMs in production. — Prior to the release of Large Language Models (LLMs) like ChatGPT that do extremely well out of the box on custom use-cases, model evaluations were fairly typical. You split your data into training/test/dev sets — trained your model on the training set, and evaluated performance on the test/dev set. I’m…

A comprehensive guide to building a customized chatbot using Generative AI, a popular vector database, prompt chaining, and UI tools — As multiple organizations are racing to build customized LLMs, a common question I have been asked is — what are the tools out there to streamline this process? In this article, I show you how to build a fully functional application for engaging in conversations through a chatbot built on…