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Showing posts with the label Fine-Tuning and Prompt Engineering

What is the Difference Between Fine-Tuning and Prompt Engineering?

What is the Difference Between Fine-Tuning and Prompt Engineering?πŸ“š In the ever-evolving world of natural language processing (NLP) and artificial intelligence, two techniques have emerged as key players in improving the performance of language models: fine-tuning and prompt engineering. These techniques are used to make models like GPT-3 even more powerful and versatile. But what exactly do they entail, and how do they differ? πŸ€” Let’s dive deep into the world of fine-tuning and prompt engineering to unravel their distinctions and understand their importance in shaping the future of NLP. Fine-Tuning: Refining the Machine MindπŸ› ️ Fine-tuning is a method used to improve the performance of pre-trained language models like GPT-3 for specific tasks or domains. It’s a bit like teaching an old dog new tricks but in the realm of AI. When a language model is pre-trained on a vast corpus of text data, it gains a general understanding of language and a wide range of concepts. However, to make i