LLM Reasoning
A language model generates text based on patterns learned during training. For simple questions, it may produce an answer directly. More complex problems can require several intermediate steps. Questi
#llms
Posts tagged #llms
LLL Evaluation
Starting with the basic question, "What is Evaluation ?"Evaluation refers to the measurement of different properties in system's outputs. What sort of properties are we interested in measuring? AI as
LLM Post-Training: From Full Fine-Tuning to PEFT, Adapters, and Soft Prompts
Large Language Models (LLMs) arrive with immense foundational knowledge acquired during pre-training. However, deploying them to specialized real-world domains—such as legal document parsing, medical
Deep Dive into LLM Pre-Training: Paradigms, Mathematical Formulations, and Training Objectives
Building effective Transformer-based Pretrained Language Models (T-PTLMs) requires understanding how models acquire general linguistic representations and adapt to specialized domains. Pre-training si
LLM Architectures: From BERT and GPT-2 to XLNet and T5
Understanding the internal mechanics of Large Language Model (LLM) architectures is crucial for building, fine-tuning, or deploying modern AI models. Why does GPT excel at text generation, while BERT
Demystifying Tokenization: From BPE and WordPiece to SentencePiece
Tokenization is the critical bridge between raw human language and numerical vector spaces in modern Large Language Models (LLMs). Before a Transformer ever sees a sentence, a tokenizer breaks down ra