HartsyInference.ModelAssets 2.0.0-alpha.156

This is a prerelease version of HartsyInference.ModelAssets.
There is a newer prerelease version of this package available.
See the version list below for details.
dotnet add package HartsyInference.ModelAssets --version 2.0.0-alpha.156
                    
NuGet\Install-Package HartsyInference.ModelAssets -Version 2.0.0-alpha.156
                    
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="HartsyInference.ModelAssets" Version="2.0.0-alpha.156" />
                    
For projects that support PackageReference, copy this XML node into the project file to reference the package.
<PackageVersion Include="HartsyInference.ModelAssets" Version="2.0.0-alpha.156" />
                    
Directory.Packages.props
<PackageReference Include="HartsyInference.ModelAssets" />
                    
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 HartsyInference.ModelAssets --version 2.0.0-alpha.156
                    
#r "nuget: HartsyInference.ModelAssets, 2.0.0-alpha.156"
                    
#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 HartsyInference.ModelAssets@2.0.0-alpha.156
                    
#: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=HartsyInference.ModelAssets&version=2.0.0-alpha.156&prerelease
                    
Install as a Cake Addin
#tool nuget:?package=HartsyInference.ModelAssets&version=2.0.0-alpha.156&prerelease
                    
Install as a Cake Tool

HartsyInference

C#/.NET inference libraries for text, images, video, speech, music, vision, 3D, and world models. Load safetensors, GGUF, and supported PyTorch checkpoints with CUDA, Vulkan, or CPU backends. Inference does not require a Python runtime; reference-generation tooling may use Python.

Alpha: pin an exact package version. Model, checkpoint-format, feature, and backend coverage differ, and implementation does not imply real-weight verification — model status records verified paths and known gaps.

Get started

For a UI, use the SwarmUI backend extension. For a .NET application, install the meta-package (or select individual packages):

dotnet add package HartsyInference --prerelease

InferenceEngine owns loading, caches, placement, and generation:

using HartsyInference.Engine;
using HartsyInference.Engine.Dispatch;
using HartsyInference.Engine.Requests;

using InferenceEngine engine = new("cuda");
ImageResult image = await engine.Images.GenerateAsync(
    new ModelSpec { Requested = "sdxl", Modality = Modality.Image, LocalPath = "sdxl.safetensors" },
    new ImageRequest { Prompt = "a castle on a mountain at sunset", Steps = 25 });
// image.Rgb contains image.Width * image.Height * 3 RGB24 bytes.

Services include Images, Text, Video, Speech, Transcribe, Music, Vision, Mesh, World, Restore, VoiceConversion, Fx, and Embeddings. Inspect the service interfaces for their request/result contracts.

CLI and HTTP

dotnet run -c Release -f net10.0 --project src/HartsyInference.Cli -- \
  image "a castle on a mountain at sunset" --model-path sdxl.safetensors -b cuda
dotnet run -c Release -f net10.0 --project src/HartsyInference.API

The CLI provides catalog/download tools and modality commands; use --help for current options. The HTTP application wraps Engine with native routes and OpenAI-compatible routes. See endpoint implementations, server options, and deployment. The HTTP text path does not currently expose the LLM package's continuous-batching scheduler.

Video supports preflight at POST /v1/native/video/plan and SSE generation at POST /v1/native/video/stream. Plans govern compatibility, artifacts, defaults, and release gates before loading weights. H3 expansion features remain subject to their individual release gates.

Configuration

Settings live in one file, ~/.config/hartsyinference/settings.json, and are read and written through hartsy settings list | get | set. The engine reads no environment variables; see settings for the knobs and their scopes.

Requirements and backends

Libraries target .NET 8 and .NET 10; building/testing uses the .NET 10 SDK. CUDA requires an NVIDIA GPU supported by the shipped PTX (baseline sm_80), a compatible driver, and required CUDA userspace libraries. Optional cuDNN paths have additional library requirements. Vulkan requires a compatible runtime and the features queried by the backend; AMD/Intel hardware validation remains open. CPU has no GPU dependency.

C# model code routes math through IBackend. CUDA uses disk-loaded PTX, Vulkan uses SPIR-V, and CPU uses SIMD with scalar fallbacks. CUDA kernels include compiled CUDA sources and legacy handwritten PTX. Vendor-library P/Invoke is used in GPU backends; this is not a ban on native driver/math libraries.

Community benchmarks

Reviewed community benchmark results

Run the same frozen workloads on your GPU and submit the complete evidence by PR. The benchmark guide covers setup, methodology and review; the explorer compares accepted runs on matching workloads. No historical scores are presented as verified community results. The image above is the checked-in dataset snapshot; it is replaced by the live explorer once Pages is activated for this repository.

Documentation

Code and packages are MIT licensed. Model weights retain their publishers' licenses; consult the checkpoint's license, including the MiniMax-H3 license, before use or redistribution.

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 is compatible.  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. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

NuGet packages (6)

Showing the top 5 NuGet packages that depend on HartsyInference.ModelAssets:

Package Downloads
HartsyInference

Meta-package for HartsyInference — a pure C#/.NET AI inference engine for text, diffusion images, speech, music, vision, video, 3D, and interactive world models. Adds all backends (CPU, CUDA, Vulkan) and modality packages in one reference.

HartsyInference.Diffusion

Image generation pipelines for HartsyInference — SD1.5, SDXL, Flux, SD3, LoRA, ControlNet, and schedulers.

HartsyInference.Vision

Vision inference for HartsyInference — CLIP embeddings, YOLO detection (planned), SAM segmentation (planned), and face detection (planned).

HartsyInference.Audio

Audio inference for HartsyInference — Whisper STT, Kokoro TTS, voice conversion, mel-spectrogram preprocessing, audio codecs, and HuggingFace model caching.

HartsyInference.LLM

Native LLM text generation for HartsyInference — a config-driven generic decoder transformer (Qwen2/Qwen3 and beyond), device-resident KV cache, sampler chain, chat templates, and a text-generation pipeline. Pure C#, programs against IBackend.

GitHub repositories

This package is not used by any popular GitHub repositories.

Version Downloads Last Updated
2.0.0-alpha.157 0 9/22/2026
2.0.0-alpha.156 0 9/22/2026
2.0.0-alpha.155 14 9/22/2026
2.0.0-alpha.154 17 9/22/2026
2.0.0-alpha.153 49 9/21/2026
2.0.0-alpha.152 54 9/21/2026
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2.0.0-alpha.149 63 9/20/2026
2.0.0-alpha.148 70 9/20/2026
2.0.0-alpha.147 62 9/20/2026
2.0.0-alpha.146 60 9/20/2026
2.0.0-alpha.145 54 9/20/2026
2.0.0-alpha.144 58 9/20/2026
2.0.0-alpha.143 55 9/20/2026
2.0.0-alpha.142 64 9/20/2026
2.0.0-alpha.141 61 9/20/2026
2.0.0-alpha.140 62 9/20/2026
2.0.0-alpha.139 59 9/20/2026
2.0.0-alpha.138 68 9/20/2026
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