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Direct weight surgery from Qwen-4B to 0.8B on an 8GB: why editing all layers breaks everything, and how 4 anchor blocks fixed it

Instead of spending weeks and billions of tokens on standard distillation, we tested an alternative: extracting layer-to-layer hidden state trajectories on a handful of calibration prompts and solving for closed-form weight updates directly in the student's MLP blocks. Key findings: Cross-architect…

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  1. 2026-10-05 18:18 · r/machinelearningnews
    Direct weight surgery from Qwen-4B to 0.8B on an 8GB: why editing all layers breaks everything, and how 4 anchor blocks fixed it

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