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turboquant

Here are 25 public repositories matching this topic...

Near-optimal vector quantization from Google's ICLR 2026 paper — 95% recall, 5x compression, zero preprocessing, pure Python FAISS replacement

  • Updated Mar 28, 2026
  • Python

Hardware-agnostic machine learning infrastructure for .NET. Implements high-performance neural network layers in C# that are transpiled to run on WebGPU, CUDA, OpenCL, WebGL, CPU, and Wasm via SpawnDev.ILGPU. Optimized for Blazor WebAssembly and native GPU execution.

  • Updated Mar 29, 2026
  • WGSL

AI agent skill implementing Google's TurboQuant compression algorithm (ICLR 2026) — 6x KV cache memory reduction, 8x speedup, zero accuracy loss. Compatible with Claude Code, Codex CLI, and all Agent Skills-compatible tools.

  • Updated Mar 28, 2026
  • Python

Near-optimal vector quantization for LLM KV cache compression. Python implementation of TurboQuant (ICLR 2026) — PolarQuant + QJL for 3-bit quantization with minimal accuracy loss and up to 8x memory reduction.

  • Updated Mar 28, 2026
  • Python

AI-powered log anomaly detection CLI — learns normal patterns, detects anomalies with semantic embeddings, matches past incidents. Powered by TurboQuant 3-bit compression (ICLR 2026).

  • Updated Mar 28, 2026
  • Python

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