HyperHRT – Instant serverless finetuning

HyperLLM offers tools for training, fine-tuning, and deploying efficient language models, as well as artificial intelligence applications based on retrieval techniques.

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HyperHRT – Instant serverless finetuning

Introduction

HyperLLM offers tools for training, tuning, and deploying efficient language models and retrieval-based AI applications.

What is HyperLLM?

HyperHRT introduces a new generation of language model architecture, developed at the Patna Institute of Technology in India. You can train, customize this architecture, and integrate it with smaller language models. HyperHRT employs real-time, decentralized fine-tuning methods. HyperCrawl, which is part of the HyperLLM project, is dedicated to establishing the infrastructure necessary for future large-scale language models. Such models require fewer computational resources and are capable of outperforming any existing models. Exthalpy is a serverless retrieval technology that will power artificial intelligence systems in the future. It enables the development of AI applications and models that place less reliance on resource-intensive training processes.

How to use HyperLLM?

Use HyperCrawl via API or install it as a Python library. Exthalpy can be utilized to develop artificial intelligence applications that focus on retrieval functions. Train and fine-tune language models using HyperHRT.

The core capabilities of HyperLLM

Real-time Decentralized Fine-Tuning (HyperHRT)
Machine-learning-based web crawler (HyperCrawl)
Serverless retrieval (Exthalpy)
Asynchronous retrieval
Data preprocessing and merging
Local embedding settings
Dense vector semantic retrieval
Management of historical data sets

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Updated：2026-11-07