# Introducing HyperLLM HyperLLM is an expedition of finding atlernate ways of building language models. LLMs that do not require high processing of training dataset to deliver hyperefficient responses. Our goal is to build really lightweight LLMs using retrieval-based architectire and that is what we are doing through our researches. In our previous attempts, we have tried replacing the whole techstack, all at once. However, we later thought of building innovative changes one by one, replacing one convectional process by an innovative one, once at a time. We have previously completed our work & learning process at Sttabot.io, Supervised.co and EternityAI. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://hyperllm.gitbook.io/hypercrawl/introducing-hyperllm.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.