Dontopedia

Training Mode

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)

Training Mode has 6 facts recorded in Dontopedia across 5 references, with 1 live disagreement.

6 facts·5 predicates·5 sources·1 in dispute

Mostly:rdf:type(2), is mx compile(1), is progressive unfreeze(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (7)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

differs-fromDiffers From(1)

modelStateModel State(1)

oppositeOfOpposite of(1)

passThroughUnchangedPass Through Unchanged(1)

setsSets(1)

setsModelToSets Model to(1)

stateState(1)

Other facts (6)

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.

6 facts
PredicateValueRef
Rdf:typeModel State[3]
Rdf:typeModel Lifecycle Stage[4]
Is Mx CompileMx Compile[1]
Is Progressive Unfreezenull[2]
Opposite ofEvaluation Mode[3]
Activated byModel.train[5]

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.

isMxCompileblah/watt-activation/part-84
ex:mx-compile
isProgressiveUnfreezeblah/watt-activation/part-176
null
typebeam/6a89aa37-552f-4aee-a292-66e6244045bc
ex:ModelState
oppositeOfbeam/6a89aa37-552f-4aee-a292-66e6244045bc
ex:evaluation-mode
typebeam/1dd18c5a-82f0-4898-9740-49697f0d9016
ex:Model-Lifecycle-Stage
activatedBybeam/0a6354af-a6f7-4051-8cb3-e50345232784
ex:model.train

References (5)

5 references
  1. [1]Part 841 fact
    ctx:discord/blah/watt-activation/part-84
  2. [2]Part 1761 fact
    ctx:discord/blah/watt-activation/part-176
  3. ctx:claims/beam/6a89aa37-552f-4aee-a292-66e6244045bc
    • full textbeam-chunk
      text/plain1 KBdoc:beam/6a89aa37-552f-4aee-a292-66e6244045bc
      Show excerpt
      self.fc2 = nn.Linear(64, 1) def forward(self, x): x = torch.relu(self.bn1(self.fc1(x))) x = self.fc2(x) return x model = RankingModel() ``` #### 3. Training Loop Improve the training loop to include va
  4. ctx:claims/beam/1dd18c5a-82f0-4898-9740-49697f0d9016
  5. ctx:claims/beam/0a6354af-a6f7-4051-8cb3-e50345232784

See also

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