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Pretraining isn't just about scaling data volume; daVinci-LLM's ablations reveal that data processing depth, domain-specific strategies, and compositional balance are equally critical for unlocking LLM capabilities.
Forget toy datasets: OpenSWE delivers 45K+ real-world, executable Python environments for leveling up your SWE agent, and it's all open-sourced.
Subtracting the mean from activations unlocks stable FP4 training for LLMs, closing the performance gap with BF16 without complex spectral methods.
