endotuning
Endotuning is a process in artificial intelligence, specifically within the domain of large language models (LLMs), that involves adjusting a pre-trained model's behavior without altering its core knowledge base. Unlike traditional fine-tuning, which modifies the model's weights through additional training on specific datasets, endotuning focuses on influencing the model's output through its input prompts or by manipulating its internal activations in a more subtle way.
One common approach to endotuning involves prompt engineering. This technique uses carefully crafted input prompts to
Another method of endotuning might involve influencing the model's internal state or attention mechanisms. This could