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SMC17/README.md

Sean Collins

Systems engineer. Pure-Zig ML infrastructure, inference kernels, and verifiable tooling.

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  1. faiss-zig faiss-zig Public

    Pure-Zig ANN — Flat, HNSW, IVFFlat, IVFPQ; L2/cosine/inner-product across all families; SIMD @Vector kernels, multi-threaded batch search. 16.94× memory compression on IVFPQ. 76 tests. No C/C++ dep…

    Zig 1

  2. inference inference Public

    Pure-Zig LLM serving — paged attention, BF16 kernels, persistent thread pool, safetensors integration. TinyLlama-1.1B end-to-end. 115 tests.

    Zig 1

  3. safetensors-zig safetensors-zig Public

    Pure-Zig safetensors reader. @Vector(32,u8) structural scan, BF16/F32/I8. 241µs parse on 201-tensor TinyLlama fixture. 21 tests.

    Zig 1

  4. tokenizers-zig tokenizers-zig Public

    Pure-Zig HF tokenizers — BPE, WordPiece, Unigram, full pipeline, offsets, tokenizer.json compat. ~5.3× faster on WordPiece. 189 tests + 600-iter fuzz.

    Zig 1