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QVAC: The future of AI is local

An exploration of the QVAC ecosystem and an invitation to developers who want more than just access to AI, those who want ownership, portability, resilience and the ability to build without asking permission.

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LoRA Fine-Tuning BitNet b1.58 LLMs on Heterogeneous Edge GPUs via QVAC Fabric

The world’s first framework to enable BitNet fine-tuning with LoRA on GPUs enabling fine-tuning on edge devices substantial performance improvements

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QVAC Genesis II: Expanding the Largest and Highest-Quality Multi-domain Educational Synthetic Dataset for LLM Pre-training

Building upon the success of Genesis I, we introduce QVAC Genesis II, a major expansion that adds new domains and a total of 148 billion tokens.

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An Edge-First Generalized LLM LoRA Fine-Tuning Framework for Heterogeneous GPUs

We present a unified, cross-platform framework that successfully enables parameter-efficient training of modern LLMs with LoRA on consumer hardware such as mobile SoCs and desktop GPUs, without relying on a CUDA-only ecosystem.

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