local model
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)
local model has 24 facts recorded in Dontopedia across 6 references, with 2 live disagreements.
Mostly:rdf:type(5), calls method(2), does skill(1)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (11)
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.
betterThanBetter Than(1)
- Frontier Model
ex:frontier-model
contrastsWithContrasts With(1)
- Frontier Model
ex:frontier-model
createsCreates(1)
- Worker Function
ex:worker-function
createsLocalInstanceCreates Local Instance(1)
- Worker Function
ex:worker-function
createsLocalModelCreates Local Model(1)
- Worker Function
ex:worker-function
generatedByGenerated by(1)
- Audio Continuation
ex:audio-continuation
mentionsMentions(1)
- Message 2026 01 30 20 14
ex:message-2026-01-30-20-14
performanceComparisonPerformance Comparison(1)
- Frontier Model
ex:frontier-model
superiorToSuperior to(1)
- Frontier Model
ex:frontier-model
usesModelUses Model(1)
- Roo Code
ex:roo-code
usesModelParametersUses Model Parameters(1)
- Local Optimizer
ex:local-optimizer
Other facts (23)
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.
| Predicate | Value | Ref |
|---|---|---|
| Rdf:type | Model | [2] |
| Rdf:type | Machine Learning Model | [3] |
| Rdf:type | Machine Learning Model | [4] |
| Rdf:type | My Model | [5] |
| Rdf:type | Neural Network Model | [6] |
| Calls Method | Model to Method | [6] |
| Calls Method | Model State Dict Method | [6] |
| Does Skill | much slower | [1] |
| Has Limitation | Slower Performance | [1] |
| Cannot Do Skill | null | [1] |
| Cannot Do | Skill | [2] |
| Does Much Slower | Skill | [2] |
| Type of | Model | [2] |
| Worse Than | Frontier Model | [2] |
| Performance | Slow | [2] |
| Has Speed | Slow | [2] |
| Low Performance | true | [2] |
| Incapable | true | [2] |
| Slow | true | [2] |
| Performance Inferiority | true | [2] |
| Property | small | [3] |
| Possessed by | Rolandnsharp7643 | [4] |
| Is Created by | Worker Function | [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.
References (6)
ctx:discord/blah/agentsofempire/part-2ctx:discord/blah/agentsofempire/2- full textctx:discord/blah/agentsofempire/2text/plain2 KB
doc:discord/blah/agentsofempire/2Show excerpt
[2026-01-30 19:58] lisamegawatts: could do a weid abstraction where the agent gets skill badges by actually doing a task and then commiting the exact workflow to a file, like you complete quest and the archivist writes your tale of glory in…
ctx:discord/blah/models/7- full textmodels-7text/plain3 KB
doc:agent/models-7/b883b3bd-bd72-412e-a054-612923d77537Show excerpt
[2025-04-28 07:38] lisamegawatts: roo code is agent team in ide, they suggest if you need another agent on your team you can input a job posting for that agent it will create the prompt for it [2025-04-28 07:40] lisamegawatts: i have it run…
ctx:discord/blah/vidya/11- full textvidya-11text/plain1 KB
doc:agent/vidya-11/eb908439-d845-412c-a434-a2eef24fee30Show excerpt
[2026-04-01 08:26] rolandnsharp7643: we're so back (files: itsOverWereBack.webp) [2026-04-01 08:50] brackishbert: <@360636009433661440> you have no idea how good that is here. I was deeply concerned of the direction that you were going in b…
ctx:claims/beam/1431835d-ed0f-4f5e-a055-310bf86b145f- full textbeam-chunktext/plain1 KB
doc:beam/1431835d-ed0f-4f5e-a055-310bf86b145fShow excerpt
def worker(data_loader): local_model = MyModel() local_optimizer = optim.Adam(local_model.parameters(), lr=0.001) update_model(local_model, local_optimizer, data_loader) return local_model.state_dict(), local_optimizer.state…
ctx:claims/beam/9151b445-41b5-4d53-900d-4199adc168c1- full textbeam-chunktext/plain1 KB
doc:beam/9151b445-41b5-4d53-900d-4199adc168c1Show excerpt
model = MyModel().to(device) optimizer = optim.Adam(model.parameters(), lr=0.001) # Define the update logic def update_model(model, optimizer, data_loader): model.train() for data, _ in data_loader: data = data.to(device) …
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