Showing 9 open source projects for "linux gpib support"

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    DeepSpec

    DeepSpec

    A full-stack codebase for training and evaluating speculative decoding

    DeepSpec is a full-stack codebase for training and evaluating draft models used in speculative decoding. It provides the components needed to prepare data, train draft models, and measure acceptance behavior against target models. The workflow starts with data preparation, including prompt download, target answer regeneration, and target cache construction. It then trains a draft model using configuration files for different algorithms and target model setups. The evaluation pipeline...
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  • 2
    DualPipe

    DualPipe

    A bidirectional pipeline parallelism algorithm

    DualPipe is a bidirectional pipeline parallelism algorithm open-sourced by DeepSeek, introduced in their DeepSeek-V3 technical framework. The main goal of DualPipe is to maximize overlap between computation and communication phases during distributed training, thus reducing idle GPU time (i.e. “pipeline bubbles”) and improving cluster efficiency. Traditional pipeline parallelism methods (e.g. 1F1B or staggered pipelining) leave gaps because forward and backward phases can’t fully overlap...
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  • 3
    YAPF

    YAPF

    A formatter for Python files

    YAPF is a Python code formatter that automatically rewrites source to match a chosen style, using a clang-format–inspired algorithm to search for the “best” layout under your rules. Instead of relying on a fixed set of heuristics, it explores formatting decisions and chooses the lowest-cost result, aiming to produce code a human would write when following a style guide. You can run it as a command-line tool or call it as a library via FormatCode / FormatFile, making it easy to embed in...
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  • 4
    Real-ESRGAN

    Real-ESRGAN

    Real-ESRGAN aims at developing Practical Algorithms

    Real-ESRGAN is a highly popular open-source project that provides practical algorithms for general image and video restoration using deep learning-based super-resolution techniques. It extends the original Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) approach by training on synthetic degradations to make results more robust on real-world images, effectively enhancing resolution, reducing noise/artifacts, and reconstructing fine detail in low-quality imagery. The...
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    Rank-BM25

    Rank-BM25

    A Collection of BM25 Algorithms in Python

    A collection of algorithms for querying a set of documents and returning the ones most relevant to the query. The most common use case for these algorithms is, as you might have guessed, to create search engines.
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  • 6
    Detectron2

    Detectron2

    Next-generation platform for object detection and segmentation

    Detectron2 is Facebook AI Research's next generation software system that implements state-of-the-art object detection algorithms. It is a ground-up rewrite of the previous version, Detectron, and it originates from maskrcnn-benchmark. It is powered by the PyTorch deep learning framework. Includes more features such as panoptic segmentation, Densepose, Cascade R-CNN, rotated bounding boxes, PointRend, DeepLab, etc. Can be used as a library to support different projects on top of it. We'll...
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  • 7
    scikit-opt

    scikit-opt

    Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing

    scikit-opt is a Python library for solving optimization problems with evolutionary and swarm-intelligence algorithms. It includes genetic algorithms, particle swarm optimization, differential evolution, simulated annealing, ant colony optimization, immune algorithms, and artificial fish swarms. The package can address continuous objectives, constrained problems, and combinatorial tasks such as the traveling salesman problem. A consistent workflow lets users define an objective, configure an...
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  • 8
    pyhanlp

    pyhanlp

    Chinese participle

    pyhanlp is a Python interface for HanLP (Han Language Processing) that lets you use a mature Java-based NLP toolkit from Python workflows without rebuilding the underlying algorithms. It is commonly used for Chinese-language NLP tasks where you want production-grade tokenization and linguistic analysis, but still want the convenience of Python scripting. The project focuses on making HanLP’s capabilities accessible through a Python-friendly API surface, so you can integrate NLP steps into...
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  • 9
    Bit operations on integers for Python - fast C implementation of bit extraction, counting, reversal etc.
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