Evaluating conversational Large Language Models (LLMs) is critical for ensuring their utility, reliability, and safety. Over the years, researchers have developed various methodologies to assess these models, each tailored to specific performance dimensions. Here, we examine the most common approaches to conversational LLM evaluation, highlighting their strengths and limitations. Automated Metrics Automated metrics offer quick […]
Fine-tuning large language models (LLMs) such as LLaMA and T5 can produce impressive results, but the memory and hardware required for traditional 16-bit fine-tuning can be a major obstacle. A new method called QLoRA (Quantized Low-Rank Adapter) changes that, enabling efficient fine-tuning on large models using much less memory. This article simplifies the core concepts […]
Large Language Models (LLMs) are becoming increasingly strong, but they also demand more computing power and energy. Researchers have created BitNet and its supporting framework, bitnet.cpp, to tackle these obstacles, providing a more intelligent approach to executing these models. In this article, we will explain the purpose of this innovative technology and how it can […]
Chatbots have rapidly become popular in recent times. These AI-based applications are easy to build yet very effective for improving customer service. Looking at the work AI, one might think that building such application must be quite challenging and costly. Talking from the R&D perspective, it is challenging and costly indeed. However, if we are […]