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   T-Tech Presents LIMe for Lower LLM Training Compute

   T-Tech researchers presented LIMe at EMNLP 2026, describing it as a lightweight attention extension that reuses key-value buffers and learns routing weights for each attention head and layer. In author-reported experiments with approximately one-billion-parameter models, LIMe matched baseline LLaMA training loss while using about 15% less compute, and the authors reported stronger results on language-modeling, multi-step-reasoning and synthetic-arithmetic benchmarks. The report also links the paper and an official implementation, but the findings primarily come from the authors’ experiments.

   r/LocalLLaMA · 🔥 0

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