@JayasriJ

LLM Pre-Training in GenAI

Apr 16, 2025 · 6 min read · In this series, we’ll explore everything about pre-training in the Generative AI (GenAI) pipeline — including how models are trained based on specific objectives or goals, and how to design an effective pre-training pipeline. But before diving into ...

RAG: 1.Basics

Apr 16, 2025 · 4 min read · Problems with Generative/FineTuning Approach: Inefficient Data Updates: Adding new data typically requires extensive retraining or fine-tuning, which can be both time-consuming and computationally expensive. Outdated Information: Generative mod...

Exploring Encoder & Decoder Types

Sep 13, 2024 · 2 min read · An Encoder-Decoder is a neural network architecture primarily used in sequence-to-sequence (seq2seq) tasks where input and output sequences can have different lengths. The model consists of two parts: Encoder: Processes the input sequence and compre...

GenAI Model Series: Basics

Aug 28, 2024 · 3 min read · In this article, we will explore only the basic models required to understand GenAI Comparison Table: ModelWhy It's UsedFeaturesLimitations 1. RNN (Recurrent Neural Network)To handle sequential data by maintaining a hidden state that captur...

Tokenization Simplified: Part-2

Aug 19, 2024 · 8 min read · This article covers the rest of the tokenization techniques, if you didn't get a chance to see part 1, it is here Types of Tokenization Techniques: Unigram Language Model: It is a probabilistic model that uses individual tokens (subwords or words)...