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LibNSC

Library for Nearest Shrunken Centroids

Forked from Libsplinter, LibNSC is a mathematical framework for creating advanced, LLM-free, and highly-accurate classification models based on natural language. It fuses Snell's Prototypical Networks with Mahalanobis distance, built on a Linux-native semantic substrate specifically written for high-signal Physics and ML vector-based data ingestion and geometric research.

Who Is It For?

LibNSC is useful to everyone from psychologists to biblical scholars to physicists, as well as trust & safety professionals and quality assurance engineers.

Current Status

Core functionality works, but needs a fully-implemented API for crypto and graphing before v1 (as well as finish forking off from Splinter).

Features

  • LLM-free, highly-accurate natural-language classification
  • Fusion of Snell's Prototypical Networks with Mahalanobis distance
  • Linux-native semantic substrate
  • High-signal ingestion for Physics and ML vector data
  • Geometric research oriented

Building and Testing

A convenience Makefile wraps the CMake build. From the repo root:

make            # configure + build (Release) into ./build
make test       # build, then run the ctest suite (unit, stress, valgrind)
make install    # build, then install (PREFIX=/usr/local by default)
make clean      # remove compiled objects/binaries, keep the build dir
make distclean  # remove the build directory and all build artifacts

Useful variables:

make BUILD_DIR=out build                       # build in a custom directory
make CMAKE_FLAGS="-DWITH_LUA=ON" build         # enable optional features
make PREFIX=/opt/libnsc install                # install elsewhere

Optional features (off by default): -DWITH_EMBEDDINGS, -DWITH_NUMA, -DWITH_LUA, -DWITH_LLAMA, -DWITH_RUST, -DWITH_WASM.

The CLI tools build into build/client/ as nsc_cli and nscp_cli, with nscctl/nscpctl convenience symlinks.

License

LibNSC is released under a mix of the Apache 2.0 and MIT software licenses, with clear delineation in file headers. See the LICENSE-APACHE and LICENSE-MIT files for full terms.

Contributing

Please see CONTRIBUTING.md.

Security

Please see SECURITY.md.

Code of Conduct

Please see CODE_OF_CONDUCT.md.

About

LibNSC is a mathematical framework for creating advanced, LLM-free, and highly-accurate classification models based on natural language. It fuses Snell's Prototypical Networks with Mahalanobis distance, built on a Linux-native semantic substrate specifically written for high-signal Physics and ML vector-based data ingestion and geometric research.

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