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<h3 id="a-flexible-framework-for-experiencing-cutting-edge-llm-inferencefine-tune-optimizations"><a class="header" href="#a-flexible-framework-for-experiencing-cutting-edge-llm-inferencefine-tune-optimizations">A Flexible Framework for Experiencing Cutting-edge LLM Inference/Fine-tune Optimizations</a></h3>
<strong><a href="#-overview">🎯 Overview</a> | <a href="#-kt-kernel---high-performance-inference-kernels">🚀 kt-kernel</a> | <a href="#-kt-sft---fine-tuning-framework">🎓 KT-SFT</a> | <a href="#-citation">🔥 Citation</a> | <a href="https://github.com/kvcache-ai/ktransformers/discussions">💬 Discussion</a> | <a href="https://github.com/kvcache-ai/ktransformers/issues/1582">🚀 Roadmap(2025Q4)</a> </strong>
<strong><a href="#-overview">🎯 Overview</a> | <a href="#-kt-kernel---high-performance-inference-kernels">🚀 kt-kernel</a> | <a href="#-kt-sft---fine-tuning-framework">🎓 KT-SFT</a> | <a href="#-citation">🔥 Citation</a> | <a href="https://github.com/kvcache-ai/ktransformers/issues/1582">🚀 Roadmap(2025Q4)</a> </strong>
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<h2 id="-overview"><a class="header" href="#-overview">🎯 Overview</a></h2>
<p>KTransformers is a research project focused on efficient inference and fine-tuning of large language models through CPU-GPU heterogeneous computing. The project has evolved into <strong>two core modules</strong>: <a href="./kt-kernel/">kt-kernel</a> and <a href="./KT-SFT/">KT-SFT</a>.</p>
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<h3 id="a-flexible-framework-for-experiencing-cutting-edge-llm-inferencefine-tune-optimizations"><a class="header" href="#a-flexible-framework-for-experiencing-cutting-edge-llm-inferencefine-tune-optimizations">A Flexible Framework for Experiencing Cutting-edge LLM Inference/Fine-tune Optimizations</a></h3>
<strong><a href="index.html#-overview">🎯 Overview</a> | <a href="index.html#-kt-kernel---high-performance-inference-kernels">🚀 kt-kernel</a> | <a href="index.html#-kt-sft---fine-tuning-framework">🎓 KT-SFT</a> | <a href="index.html#-citation">🔥 Citation</a> | <a href="https://github.com/kvcache-ai/ktransformers/discussions">💬 Discussion</a> | <a href="https://github.com/kvcache-ai/ktransformers/issues/1582">🚀 Roadmap(2025Q4)</a> </strong>
<strong><a href="index.html#-overview">🎯 Overview</a> | <a href="index.html#-kt-kernel---high-performance-inference-kernels">🚀 kt-kernel</a> | <a href="index.html#-kt-sft---fine-tuning-framework">🎓 KT-SFT</a> | <a href="index.html#-citation">🔥 Citation</a> | <a href="https://github.com/kvcache-ai/ktransformers/issues/1582">🚀 Roadmap(2025Q4)</a> </strong>
</div>
<h2 id="-overview"><a class="header" href="#-overview">🎯 Overview</a></h2>
<p>KTransformers is a research project focused on efficient inference and fine-tuning of large language models through CPU-GPU heterogeneous computing. The project has evolved into <strong>two core modules</strong>: <a href="./kt-kernel/">kt-kernel</a> and <a href="./KT-SFT/">KT-SFT</a>.</p>
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