Why I Built a Native ML Inference Engine in Rust
Kjarni is a single native library that runs transformer models in your own process, from Rust, C#, Go, C++ or the command line. One install, on CPU, offline after the first run.
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Kjarni is a single native library that runs transformer models in your own process, from Rust, C#, Go, C++ or the command line. One install, on CPU, offline after the first run.
Read moreRun sentiment analysis locally in C# using transformer models. Positive, negative, neutral, emotions, toxicity. Three lines of code, one NuGet package, running on your own machine.
Read moreAdd semantic search to your C# app in 5 lines. Match text by meaning, not keywords. One NuGet package with zero dependencies, running on CPU in your own process.
Read moreBuild a full-text search engine in C# with keyword search, semantic search, hybrid ranking, and reranking. Index files and query them in 10 lines of code, with the index living on your own disk.
Read moreRun sentiment analysis, generate embeddings, detect toxicity, and search documents from your terminal. One binary, reads stdin, writes JSON, pipes into any script or CI pipeline.
Read moreImplement IEmbeddingGenerator locally in .NET. Plug Kjarni into Microsoft.Extensions.AI and Semantic Kernel with one NuGet package that has zero dependencies. Runs on CPU, in your process, offline.
Read moreRun Llama, Mistral, Qwen or Phi locally from C#. One NuGet package, loaded in-process and answering offline. Streaming, multi-turn conversations and sampling control in .NET.
Read moreThree config files disagree about how long an all-MiniLM-L6-v2 input can be, and the answer sentence-transformers uses is 256 tokens. At a 1000-character chunk size, 87% of chunks are longer than that, and the excess is discarded silently.
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