LoRA (Low-Rank Adaptation) and fine-tuning are two methods to adapt large language models (LLMs) to specific tasks or domains. LLMs are pre-trained on massive amounts of general domain data, such as GPT-3, RoBERTa, and DeBERTa, and have shown impressive performance on various natural language processing (NLP) tasks. Why fine tune a LLM? Fine-tuning of LLMs...
Tag: LLMs
Super Apps vs. Large Language Models
In the rapidly evolving world of software, Super Apps and Large Language Models (LLMs) offer two distinct approaches to address user needs and preferences. Super Apps, like WeChat, consolidate various functions and services into a single platform, while LLMs, such as GPT from OpenAI promise a new era of software adaptability through self-modifying code generation....
Why Large Language Models will replace Apps
The dawn of large language models (LLMs) like GPT from OpenAI that can write their own code and adapt to novel requirements promises a more flexible approach to software development. In this article, we will explore in detail why apps as we know them will soon be a thing of the past and how LLMs...
