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If every layer prefix is a valid model, why do we still pick a size at deploy time?

I keep four checkpoints of the same family on disk: a 1.5B, an 8B, a 32B, and a 70B. Four training runs I didn't do, four eval suites I have to trust on faith, four quantized copies, four latency…

  • Multiple model checkpoints (1.5B, 8B, 32B, 70B) exist on disk for different tasks.
  • Decision at deploy time relies on manual rules, not optimal for all use cases.
  • Telescopic models propose single artifact with multiple depths, but validity verification needed.

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