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    <description>Engineering notes on quantization, serving, evaluation and supply-chain verification for open-weight models.</description>
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      <title>Quantizing models without losing the edge cases</title>
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      <description>Perplexity moves by a fraction of a point after quantization. Production incidents do not. A practical checklist for validating Q4 builds.</description>
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      <title>Serving a 70B mixture-of-experts model on a single workstation</title>
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      <description>Expert offload, page cache pressure and the routing behaviour that surprised us on a 24 GB accelerator.</description>
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      <title>Why we publish an eval harness with every release</title>
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      <description>Benchmark tables age badly. Shipping the harness means a result can be reproduced instead of trusted.</description>
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      <title>Token economics: batching, the KV cache and the p99 cliff</title>
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      <description>How continuous batching, prefix caching and admission control interact under a burst.</description>
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      <title>Fine-tuning small models on a budget</title>
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      <description>A LoRA workflow that fits on two consumer GPUs and produces adapters worth shipping.</description>
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      <title>How uploaded weights get verified</title>
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      <description>Hashing, format inspection, tokenizer consistency, smoke inference and the publication gate.</description>
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