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Achievement: Pair ExtraordinaireAchievement: Pull Sharkx2

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jontb/README.md

Jonathan Borenstein

M.Math in Statistics, University of Waterloo
Random matrix theory, numerical computing, machine learning

LinkedIn · X · ORCID · Email

Selected work: FiniteFree, a Python library for finite free probability (PyPI)

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  1. FiniteFree FiniteFree Public

    Python tools for finite free probability, random matrix sampling and spectral computation.

    Python 1

  2. vllm-project/llm-compressor vllm-project/llm-compressor Public

    State-of-the-art LLM compression, built for production inference with vLLM

    Python 4k 729

  3. pymc-labs/pymc-marketing pymc-labs/pymc-marketing Public

    Bayesian marketing toolbox in PyMC. Media Mix (MMM), customer lifetime value (CLV), buy-till-you-die (BTYD) models and more.

    Python 1.3k 437

  4. pymc-labs/CausalPy pymc-labs/CausalPy Public

    A Python package for causal inference in quasi-experimental settings

    Python 1.2k 126

  5. ai-dynamo/aiperf ai-dynamo/aiperf Public

    AIPerf is a comprehensive benchmarking tool that measures the performance of generative AI models served by your preferred inference solution.

    Python 857 259

  6. llm-d/llm-d-router llm-d/llm-d-router Public

    llm-d Router: The intelligent entry point for inference requests

    Go 459 516

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