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 moreall-MiniLM-L6-v2 truncates at 256 tokens, about 900 characters, and drops the rest without a warning. Why the configs say 128, 256 and 512, what chunk size to use, and why raising max_seq_length to 512 makes retrieval worse.
Read moreRun embeddings, classification and reranking from C++ with no libtorch and no ONNX Runtime: one header and one shared library that links only against libc. Works with C++11, C++14, C++17 and C++23, and takes four commands from nothing to output.
Read moreLoad Llama, Mistral, Qwen or Phi inside a C++ program and generate text in-process. One header and one shared library, blocking replies and token streaming, with the model running on your own machine.
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