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Freeze an identity-selected GSM8K startup/recovery profile and let the existing qualification launcher select separate trainer/rollout GPUs while retaining the legacy resident default. Preserve the original Thinking/RLTT packets and label CPU command checks separately from pending real backend acceptance. Signed-off-by: 0z5a <dezhen.lu@student.uni-tuebingen.de>
Signed-off-by: 0z5a <dezhen.lu@student.uni-tuebingen.de>
Signed-off-by: 0z5a <dezhen.lu@student.uni-tuebingen.de>
Signed-off-by: 0z5a <dezhen.lu@student.uni-tuebingen.de>
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RFC465 starts with ordinary Ouro GRPO through the standard
train.pyandRolloutManager, with separate trainer and rollout resources. The existing qualification recipe always selects resident colocation and the Thinking/RLTT packet, so it cannot directly establish that initial support profile.Add an identity-selected ordinary-Ouro K4/FP32 GRPO startup/recovery packet and an explicit resource-layout choice while preserving the resident default and all existing Thinking inputs. The profile keeps three updates, 96 new training completions per logical run and a continuous-versus-fresh-process comparison. No reference, critic, KL, early exit or speculation is included. The small launcher change reuses the existing source/model/state/output audit chain.
Validation retains exact source/input/metadata and wheel-RECORD hashes, XML and original local wait records. No model weight bodies or remote environment changes are added. CPU command checks are explicitly separated from backend acceptance and convergence evidence.
Stacked on draft #36 (
ops/scalerlt-initial-paper-v01at a6c0b51). Only this acceptance-preparation increment is included. The current experimental RLT pin and pending upstream dependency acceptance are documented.