Dontopedia

Evaluated Model

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-09.)

Evaluated Model has 6 facts recorded in Dontopedia across 2 references, with 1 live disagreement.

6 facts·5 predicates·2 sources·1 in dispute

Mostly:rdf:type(2), has parameter count(1), has decode architecture type(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (2)

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.

hasOutputHas Output(1)

producesProduces(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:typeAssessed Model[2]
Rdf:typeFinal Model[2]
Has Parameter Count108000000[1]
Has Decode Architecture TypeO(1) recurrent[1]
Has Decode Statecompiled[1]
Has Effective Parameter Count37400000[1]

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.

hasParameterCountblah/watt-activation/162
108000000
hasDecodeArchitectureTypeblah/watt-activation/162
O(1) recurrent
hasDecodeStateblah/watt-activation/162
compiled
hasEffectiveParameterCountblah/watt-activation/162
37400000
typebeam/2155073f-6f86-4661-a2c4-49d7e078edee
ex:AssessedModel
typebeam/2155073f-6f86-4661-a2c4-49d7e078edee
ex:FinalModel

References (2)

2 references
  1. [1]1624 facts
    ctx:discord/blah/watt-activation/162
    • full textwatt-activation-162
      text/plain2 KBdoc:agent/watt-activation-162/60b4e03a-418d-44da-a803-c9585844c73e
      Show excerpt
      [2026-03-09 18:40] xenonfun: ⏺ Here's my assessment: Speed: Excellent - 265 tok/s decode on M2 Ultra (idle), 14-27ms prefill. Very fast for 108M params. The compiled O(1) recurrent decode is working well.
  2. ctx:claims/beam/2155073f-6f86-4661-a2c4-49d7e078edee
    • full textbeam-chunk
      text/plain1 KBdoc:beam/2155073f-6f86-4661-a2c4-49d7e078edee
      Show excerpt
      - Define training arguments for the `Trainer` to control the training process. 5. **Trainer**: - Use the `Trainer` from the `transformers` library to fine-tune the model. 6. **Fine-Tuning and Evaluation**: - Fine-tune the model o

See also

Keep researching

Missing something or suspicious of what's here? Kick off a research session — a Claude agent will investigate, cite its sources, and file new facts into a dedicated context you can review before accepting into the shared view.