Language Models - Labellerr

Language Models

A collection of 6 posts

Baidu’s ERNIE 4.5 & X1: Are They China’s Answer to GPT-4?

Baidu’s Ernie 4.5 Outperforms GPT 4.5 By A Mile

Baidu’s ERNIE 4.5 & X1 signal China’s relentless AI expansion. Following DeepSeek R1 and Manus AI, these new models aim to challenge global AI leaders. Can they compete with OpenAI’s GPT-4 and beyond?

Training Small-Scale Vs Large-Scale Language Models: The Difference

Large Language Models

Training Small-Scale Vs Large-Scale Language Models: The Difference

Explore the contrasts between training small and large-scale language models, from data requirements and computational power to model complexity and performance nuances in NLP applications

silicon board shaped as human brain

Language Models

Exploring Architectures and Configurations for Large Language Models (LLMs)

Large Language Models (LLMs) like GPT-4 excel in NLP tasks through advanced architectures, including encoder-decoder, causal decoder, and prefix decoder. This article delves into their configurations, activation functions, and training stability for optimal performance.

DragGAN AI-powered tool for image editing and manipulation

Language Models

DragGAN: An AI Magic Tool For Editing Images

Welcome to the enchanted world of DragGAN, where magic and artificial intelligence combine to create masterpieces from seemingly ordinary photographs. This blog explores the fascinating powers of DragGAN, an AI-driven wizard with the dexterous ability to magically give your images a life of their own. Join us on this enthralling

RoBERTa: A Robustly Optimized BERT Pretraining Approach

Language Models

RoBERTa: A Robustly Optimized BERT Pretraining Approach

Keeping up with the latest developments in the rapidly expanding field of natural language processing is challenging. But fear not—a strong ally is on hand to completely alter the way we think about language comprehension. Welcome to RoBERTa, the robustly optimized BERT pretraining approach set to revolutionize NLP. Join

Secret To Enhance Performance and Task Generalization in LLMs

Large Language Models

How To Enhance Performance and Task Generalization in LLMs

From the previous blog, we studied that Pre-training forms the foundation of LLMs' abilities. LLMs acquire crucial language comprehension and generation skills through pre-training on extensive corpora. The size and quality of the pre-training corpus play a vital role in enabling LLMs to possess powerful capabilities. Moreover, the design