About This Site
HyperLLM offers tools for training, tuning, and deploying efficient language models and retrieval-based AI applications. HyperHRT introduces a new generation of language model architecture developed at the Indian Institute of Technology, Patna that you can train & tune and integrate with a small-language model. HyperHRT works on real-time decentralised fine-tuning approach. HyperCrawl is a part of HyperLLM where they are dedicated to build the infrastructure for a world of future LLMs. Models that requires less computational resources & outperforms any models available. Exthalpy is serverless retrieval to power the future of AI. Build retrieval-first AI applications and models that are less dependent on computation-heavy training processes.
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Key Features AI
Core Features
Real-time decentralised fine-tuning (HyperHRT)
ML-first web crawler (HyperCrawl)
Serverless retrieval (Exthalpy)
Asynchronous Retrieval
Data Preprocessing & Merging
Local Embedding Setup
Dense Vector Semantic Retrieval
Historical Dataset Management
Advantages
Reduces computation-heavy training processes
Eliminates crawl time of domains
Offers asynchronous retrieval for faster processing
Supports local embedding setup
Provides historical dataset management
Available as an API and Python library
Open-source and free to use
缺点：May require technical expertise to implement
缺点：Limited information on specific performance metrics
缺点：Reliance on external infrastructure (e.g., Google Colab, Jupyter Notebook)
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