I recently embarked on an exciting research journey to explore the vulnerabilities of large language models (LLMs) like ChatGPT, Anthropic Gemini, and similar models. My goal was to see how hackers could exploit them through prompt injection attacks.
In the ever-evolving domain of Natural Language Processing (NLP), supervised fine-tuning has emerged as a game-changing technique for adapting pre-trained Large Language Models (LLMs) to specific tasks. While pre-trained LLMs like those in the GPT family have made significant strides in language comprehension and generation, they often lack optimization for particular applications.
LLama is undoubtably one of the best open-source LLM out there by Meta. If you have ever wandered how it works, how these LLMs are able to produce human like text and talk like humans. Well, you are not alone.
