Dontopedia

Resume Instruction

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-06.)

Resume Instruction has 10 facts recorded in Dontopedia across 3 references, with 1 live disagreement.

10 facts·9 predicates·3 sources·1 in dispute

Mostly:involves(2), uses same(1), from checkpoint(1)

Maturity scale raw canonical shape-checked rule-derived certified

Other facts (10)

The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.

10 facts
PredicateValueRef
Involvesreset counters[3]
Involvessame settings[3]
Uses SameSettings[1]
From CheckpointFull Checkpoint 60k[1]
Involves ResettingCounters[1]
Probably HelpsTraining[1]
Advises Kill and RelaunchWith Resume From Path[2]
ActionResume from there[3]
TargetLatest Full Checkpoint[3]
Predicted Outcomehelp[3]

Timeline

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

usesSameblah/watt-activation/part-41
ex:settings
fromCheckpointblah/watt-activation/part-41
ex:full-checkpoint-60k
involvesResettingblah/watt-activation/part-41
ex:counters
probablyHelpsblah/watt-activation/part-41
ex:training
advisesKillAndRelaunchblah/watt-activation/part-659
ex:with-resume-from-path
actionblah/watt-activation/41
Resume from there
targetblah/watt-activation/41
ex:latest-full-checkpoint
involvesblah/watt-activation/41
reset counters
involvesblah/watt-activation/41
same settings
predictedOutcomeblah/watt-activation/41
help

References (3)

3 references
  1. [1]Part 414 facts
    ctx:discord/blah/watt-activation/part-41
  2. [2]Part 6591 fact
    ctx:discord/blah/watt-activation/part-659
  3. [3]415 facts
    ctx:discord/blah/watt-activation/41
    • full textwatt-activation-41
      text/plain2 KBdoc:agent/watt-activation-41/72feaad1-da4d-405f-9a39-dc01405b6065
      Show excerpt
      [2026-03-07 04:39] xenonfun: ### Validation Perplexity: The gold standard for "best" tracking is eval loss on a held-out set — data the model never trains on. You periodically pause, run the model over the val set with no gradient upda

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