EvaluatedApplications.AlgFormer 1.2.0

.NET 8.0

dotnet add package EvaluatedApplications.AlgFormer --version 1.2.0

NuGet\Install-Package EvaluatedApplications.AlgFormer -Version 1.2.0

This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package.

<PackageReference Include="EvaluatedApplications.AlgFormer" Version="1.2.0" />

For projects that support PackageReference, copy this XML node into the project file to reference the package.

<PackageVersion Include="EvaluatedApplications.AlgFormer" Version="1.2.0" />
                    

                            Directory.Packages.props

<PackageReference Include="EvaluatedApplications.AlgFormer" />
                    

                            Project file

For projects that support Central Package Management (CPM), copy this XML node into the solution Directory.Packages.props file to version the package.

paket add EvaluatedApplications.AlgFormer --version 1.2.0

The NuGet Team does not provide support for this client. Please contact its maintainers for support.

#r "nuget: EvaluatedApplications.AlgFormer, 1.2.0"

#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package.

#:package EvaluatedApplications.AlgFormer@1.2.0

#:package directive can be used in C# file-based apps starting in .NET 10 preview 4. Copy this into a .cs file before any lines of code to reference the package.

#addin nuget:?package=EvaluatedApplications.AlgFormer&version=1.2.0
                    

                            Install as a Cake Addin

#tool nuget:?package=EvaluatedApplications.AlgFormer&version=1.2.0
                    

                            Install as a Cake Tool

The NuGet Team does not provide support for this client. Please contact its maintainers for support.

AlgFormer

The reusable algebraic-transformer engine from PrismFormer — define a learning model, train it, and run inference. Pure double[] + SIMD, no external ML runtime or native dependency. Data-parallel training runs through an EvalApp pipeline (resource-gated and adaptively tuned); model geometry defaults come from the Phasor VSA codec.

This is the engine only — the tokenizer, the frozen production spec, the data-source adapters, and the distributed swarm from the full PrismFormer app are intentionally not included.

Usage

using PrismFormer;

// define a model (tokens are ints; feed your own encoding)
var model = new AlgFormer(vocab: 16, shifts: 4, layers: 2, maxContext: 6, dModel: 32, frozenPrefix: 0);

// train — data is IReadOnlyList<(int[] Ctx, int Target)>
var trainer = new PrismTrainer(model);                 // data-parallel via EvalApp
double loss = trainer.TrainEpoch(data, batchSize: 64, lr: 5e-2, shuffleSeed: 1);
//   or model-native: model.TrainStep / model.TrainEpoch / model.Train

// inference
int next     = model.Predict(context);                 // argmax next token
double[] lg  = model.LogitsFor(context);
int[] sample = model.Generate(prompt, maxNewTokens: 20, temperature: 0.8);

Set model.Map = PrismEval.Cpu to fan a single generate across cores; training keeps Map sequential (it is already batch-parallel). Training runs data-parallel through EvalApp with the adaptive tuner on by default — no key needed.

License

Proprietary — this package ships the compiled library only; source is not distributed. Every capability in it is free to use; a license key is reserved for future advanced features (none are gated today). See LICENSE. Copyright (c) 2026 Dongyang Stephen Chen, trading as Evaluated Applications. All rights reserved.

Product	Compatible and additional computed target framework versions.
.NET	net8.0 is compatible. net8.0-android was computed. net8.0-browser was computed. net8.0-ios was computed. net8.0-maccatalyst was computed. net8.0-macos was computed. net8.0-tvos was computed. net8.0-windows was computed. net9.0 was computed. net9.0-android was computed. net9.0-browser was computed. net9.0-ios was computed. net9.0-maccatalyst was computed. net9.0-macos was computed. net9.0-tvos was computed. net9.0-windows was computed. net10.0 was computed. net10.0-android was computed. net10.0-browser was computed. net10.0-ios was computed. net10.0-maccatalyst was computed. net10.0-macos was computed. net10.0-tvos was computed. net10.0-windows was computed.

Product

.NET

Compatible target framework(s)

Included target framework(s) (in package)

Learn more about Target Frameworks and .NET Standard.

net8.0
- EvaluatedApplications.EvalApp (>= 1.4.3)
- EvaluatedApplications.Phasor (>= 1.0.1)

NuGet packages (3)

Showing the top 3 NuGet packages that depend on EvaluatedApplications.AlgFormer:

Package	Downloads
EvaluatedApplications.AlgFormer.Gpu Optional ILGPU/CUDA acceleration for the AlgFormer package's HoloFormer: batched GPU forward + backward training (GpuHoloTrainer) and GPU inference (Logits), with automatic CPU fallback when no CUDA device is present (GpuDevice.HasGpu). Add this package only if you want GPU training; the core AlgFormer stays dependency-free and AOT/trim-safe without it.	254
EvaluatedApplications.Prose Grammar-driven synthetic corpus generator: mines nouns, verbs and adjectives and the syntax that joins them from real text with the rules of grammar, stores them in HoloDb, and recombines them into new, grammatical, plausible sentences. Rules-first (deterministic, zero-training); an optional mini-HoloFormer breaks residual tagging ambiguity and scores plausibility.	69
EvaluatedApplications.EvalApp.Neural An always-learning neural concurrency tuner for EvalApp. A tiny holographic policy model (HoloFormer, ~0.4ms/decision) tunes resource-gate concurrency online and reacts in real time as conditions change; it ships warm and keeps learning. It matches the built-in heuristic on lean/clean pipelines and beats it on real coupled workloads (~25% faster on a multi-gate DB + disk + CPU benchmark). Opt in with .WithNeuralTuning() on your app.	56

GitHub repositories

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