Open post LoRA and Finetuning

LoRA vs. Fine-Tuning LLMs

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...

Open post Super Apps vs Large Language Models

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....

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