Dontopedia

Mistral large base

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

Mistral large base has 17 facts recorded in Dontopedia across 5 references, with 2 live disagreements.

17 facts·12 predicates·5 sources·2 in dispute

Mostly:has(2), is(2), receives input from(2)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (9)

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.

isIs(2)

providesDescriptionToProvides Description to(2)

fedToMainModelFed to Main Model(1)

feedsIntoFeeds Into(1)

providesOutputToProvides Output to(1)

suppliedBeforeMainResponseGenerationSupplied Before Main Response Generation(1)

targetTarget(1)

Other facts (16)

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.

16 facts
PredicateValueRef
HasCustom Semantic Dialogue Training[1]
HasCustom Semantic Dialogue Training[4]
IsMain Language Generator[1]
IsMain Language Generator[4]
Receives Input FromMistral Pixtral[5]
Receives Input FromMistral 7b[5]
Processing StepInstruction Processing[5]
Processing StepMemory Retrieval[5]
Custom Semantic Dialogue Trainingtrue[2]
Creates Responses FromInput and Retrieved Context[3]
Is Primary Language Generatortrue[3]
References Real ModelMistral AI[4]
Rdf:typeModel[5]
Has Custom TrainingSemantic Dialogue Training[5]
System RoleMain Language Generator[5]
Generates OutputResponse[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.

hasblah/blocks/part-9
ex:custom-semantic-dialogue-training
isblah/blocks/part-9
ex:main-language-generator
customSemanticDialogueTrainingblah/blocks/part-2
true
createsResponsesFromblah/omega/part-844
ex:input-and-retrieved-context
isPrimaryLanguageGeneratorblah/omega/part-844
true
hasblah/omega/part-843
ex:custom-semantic-dialogue-training
isblah/omega/part-843
ex:main-language-generator
referencesRealModelblah/omega/part-843
ex:mistral-ai
typeblah/omega/837
ex:Model
labelblah/omega/837
Mistral large base
hasCustomTrainingblah/omega/837
ex:semantic-dialogue-training
systemRoleblah/omega/837
ex:main-language-generator
receivesInputFromblah/omega/837
ex:mistral-pixtral
receivesInputFromblah/omega/837
ex:mistral-7b
processingStepblah/omega/837
ex:instruction-processing
processingStepblah/omega/837
ex:memory-retrieval
generatesOutputblah/omega/837
ex:response

References (5)

5 references
  1. [1]Part 92 facts
    ctx:discord/blah/blocks/part-9
  2. [2]Part 21 fact
    ctx:discord/blah/blocks/part-2
  3. [3]Part 8442 facts
    ctx:discord/blah/omega/part-844
  4. [4]Part 8433 facts
    ctx:discord/blah/omega/part-843
  5. [5]8379 facts
    ctx:discord/blah/omega/837
    • full textomega-837
      text/plain2 KBdoc:agent/omega-837/09ff7339-3969-4b55-8739-569141d3d630
      Show excerpt
      [2026-01-12 20:47] therosegoblin: <@1438866165475708979> So. If you’re interested in the architecture I’m building here’s a quick overview of how it works. I have trained a family of Mistral base models through supervised learning on data

See also

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