MyModel

as donto believed on

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

MyModel has 90 facts recorded in Dontopedia across 13 references, with 7 live disagreements.

90 facts·56 predicates·13 sources·7 in dispute

Mostly:rdf:type(13), has layer(8), used for(4)

Rdf:typein dispute`rdf:type`

Neural Network Model^[1]all time · 5002a4e3 4556 403f 86e2 22d5643a5538
Machine Learning Model^[2]all time · 48293708 B5c3 49a0 B365 C9176ea0152f
Machine Learning Model^[4]all time · C4e05e80 6f07 4d9c 9796 7f9111b19071
Machine Learning Model^[6]all time · 89848f08 0044 49af 9ee8 02356dc4e8be
Neural Network^[7]all time · E949b3bf 5972 4a2e Ac8c 633577808057
Model^[7]all time · E949b3bf 5972 4a2e Ac8c 633577808057
Machine Learning Framework^[8]all time · F537c0ec 0996 4601 868a 9cb050537ebd
Neural Network^[9]all time · Cce29709 18fd 476c 8bcc De705b470912
Machine Learning Model^[10]all time · 2b55433d F10b 4ba8 Ac07 7b8a156dc333
Sequential^[11]all time · B37d3f65 B489 4a88 Aa05 62e2c014851e

Inbound mentions (30)

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.

`belongsTo`Belongs to(5)

Linear Layer 1ex:linear-layer-1
Linear Layer 2ex:linear-layer-2
Linear Layer 3ex:linear-layer-3
Relu Activation 1ex:relu-activation-1
Relu Activation 2ex:relu-activation-2

`isPartOf`Is Part of(4)

Layer 1ex:layer-1
Layer 2ex:layer-2
Leaky Relu Activationex:leaky-relu-activation
Relu Activationex:relu-activation

`appliesTo`Applies to(3)

99.8% Stabilityex:99.8% stability
Hyperparameter Configex:hyperparameter-config
Latency Logging Integrationex:latency-logging-integration

`hasPart`Has Part(3)

Layer 1ex:layer-1
Layer 2ex:layer-2
Leaky Relu Activationex:leaky-relu-activation

`usedFor`Used for(2)

Loss Functionex:loss-function
Optimizerex:optimizer

`appliedTo`Applied to(1)

Loss Functionex:loss-function

`are-related-to`Are Related to(1)

Language Embeddingsex:language-embeddings

`domainOf`Domain of(1)

Language Embeddingsex:language-embeddings

`executesOn`Executes on(1)

Forward Passex:forward-pass

`hasExistingModel`Has Existing Model(1)

Userex:user

`isExampleOf`Is Example of(1)

Scoring Model Classex:scoring-model-class

`isOutputOf`Is Output of(1)

Language Embeddingslanguage-embeddings

`method-of`Method of(1)

Model Evalex:model-eval

`optimizes`Optimizes(1)

Optimizerex:optimizer

`partOf`Part of(1)

Resizing Logicex:resizing-logic

`updates`Updates(1)

Optimizerex:optimizer

`usesModel`Uses Model(1)

Training Loopex:training-loop

`usesParameter`Uses Parameter(1)

Optimizerex:optimizer

Other facts (72)

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.

72 facts

Predicate	Value	Ref
Has Layer	Linear Layer 1	[7]
Has Layer	Relu Activation 1	[7]
Has Layer	Linear Layer 2	[7]
Has Layer	Relu Activation 2	[7]
Has Layer	Linear Layer 3	[7]
Has Layer	Linear Layer 1	[12]
Has Layer	Relu Layer	[12]
Has Layer	Linear Layer 2	[12]
Used for	Semantic Analysis	[2]
Used for	Semantic Analysis	[3]
Used for	Language Embeddings	[4]
Used for	Reranking	[7]
Has Improvement	Data Loading Preprocessing	[5]
Has Improvement	Training Loop	[5]
Has Improvement	Evaluation Monitoring	[5]
Has Improvement	Resource Management	[5]
Consists of	Layer 1	[11]
Consists of	Relu Activation	[11]
Consists of	Leaky Relu Activation	[11]
Consists of	Layer 2	[11]
Benefits From	Performance Enhancement	[5]
Benefits From	Stability Enhancement	[5]
Training Mode	true	[1]
Evaluation Mode	true	[1]
Has Stability Metric	99.6	[2]
Tested Over	2000	[2]
Has Performance Characteristic	Stability	[2]
Contrast With	Latency Concern	[2]
Performance Concern	Latency	[3]
Is Subject of	Compliance Improvement	[4]
Purpose	Language Embeddings	[5]
Has Version	2.1.2	[6]
Has Component	Resizing Logic	[6]
Has Part	Resizing Logic	[6]
Has Software Version	2.1.2	[6]
Is Instanceof	Torch.nn.sequential	[7]
Moved to	Device	[7]
Integrated With	Keycloak	[7]
Has Forward Pass	true	[8]
Framework	PyTorch	[9]
Class Name	MyModel	[9]
Inherits From	nn.Module	[9]
Has First Layer	Fc1 Layer	[9]
Has Second Layer	Fc2 Layer	[9]
Activation Function	ReLU	[9]
Forward Pass Sequence	fc1 then fc2	[9]
Architecture Type	feedforward	[9]
Uses Activation	Re Lu	[9]
Data Flow	Forward Sequence	[9]
Implemented in	Python	[9]
Uses Framework	PyTorch	[9]
Total Parameters	66562	[9]
Architecture Category	simple-feedforward	[9]
Implementation Status	incomplete	[9]
Import Statement	import torch.nn as nn	[9]
Code Completeness	truncated	[9]
Network Depth	two-layers	[9]
Has Parameter	128	[11]
Is Set to Training Mode	true	[11]
Uses Optimizer	Optimizer	[11]
Uses Loss Function	Loss Function	[11]
Is in Training State	true	[11]
Is Defined in	Code Example 9564	[12]
Has Total Layers	3	[12]
Architecture	Sequential	[12]
Input Dimension	128	[12]
Output Dimension	10	[12]
Has Sequential Structure	true	[12]
Initialization	Sequential Initialization	[13]
Located on	Gpu Device	[13]
Has Parameter Count	3	[13]
Requires	Cuda Device	[13]

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.

90 undated

—

typebeam/5002a4e3-4556-403f-86e2-22d5643a5538

ex:NeuralNetworkModel

—

trainingModebeam/5002a4e3-4556-403f-86e2-22d5643a5538

true

—

evaluationModebeam/5002a4e3-4556-403f-86e2-22d5643a5538

true

—

typebeam/48293708-b5c3-49a0-b365-c9176ea0152f

ex:MachineLearningModel

—

usedForbeam/48293708-b5c3-49a0-b365-c9176ea0152f

ex:semantic-analysis

—

hasStabilityMetricbeam/48293708-b5c3-49a0-b365-c9176ea0152f

99.6

—

testedOverbeam/48293708-b5c3-49a0-b365-c9176ea0152f

2000

—

hasPerformanceCharacteristicbeam/48293708-b5c3-49a0-b365-c9176ea0152f

ex:stability

—

contrastWithbeam/48293708-b5c3-49a0-b365-c9176ea0152f

ex:latency-concern

—

usedForbeam/c4b521c9-43a8-4387-af25-03c84b4c45ab

ex:semantic-analysis

—

performance-concernbeam/c4b521c9-43a8-4387-af25-03c84b4c45ab

ex:latency

—

is-subject-ofbeam/c4e05e80-6f07-4d9c-9796-7f9111b19071

ex:compliance-improvement

—

typebeam/c4e05e80-6f07-4d9c-9796-7f9111b19071

ex:MachineLearningModel

—

usedForbeam/c4e05e80-6f07-4d9c-9796-7f9111b19071

ex:language-embeddings

—

hasImprovementbeam/4787fe87-1198-4568-ad3b-9fa2441fb1e0

ex:data-loading-preprocessing

—

hasImprovementbeam/4787fe87-1198-4568-ad3b-9fa2441fb1e0

ex:training-loop

—

hasImprovementbeam/4787fe87-1198-4568-ad3b-9fa2441fb1e0

ex:evaluation-monitoring

—

hasImprovementbeam/4787fe87-1198-4568-ad3b-9fa2441fb1e0

ex:resource-management

—

purposebeam/4787fe87-1198-4568-ad3b-9fa2441fb1e0

ex:language-embeddings

—

benefitsFrombeam/4787fe87-1198-4568-ad3b-9fa2441fb1e0

ex:performance-enhancement

—

benefitsFrombeam/4787fe87-1198-4568-ad3b-9fa2441fb1e0

ex:stability-enhancement

—

typebeam/89848f08-0044-49af-9ee8-02356dc4e8be

ex:MachineLearningModel

—

hasVersionbeam/89848f08-0044-49af-9ee8-02356dc4e8be

2.1.2

—

hasComponentbeam/89848f08-0044-49af-9ee8-02356dc4e8be

ex:resizing-logic

—

hasPartbeam/89848f08-0044-49af-9ee8-02356dc4e8be

ex:resizing-logic

—

hasSoftwareVersionbeam/89848f08-0044-49af-9ee8-02356dc4e8be

2.1.2

—

typebeam/e949b3bf-5972-4a2e-ac8c-633577808057

ex:NeuralNetwork

—

labelbeam/e949b3bf-5972-4a2e-ac8c-633577808057

Sequential Model

—