2 个仓库
High-throughput processing of massive text datasets using multi-threaded execution.
Distinct from Large-Scale Text Handling: The candidates focus on memory-efficient string handling or UI rendering, not multi-threaded execution engines for bulk file processing.
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pkuseg-python is a Chinese word segmentation toolkit and natural language processing library. It provides specialized models for splitting Chinese text into words across various domains, including news, medical, and web content, and includes a tool for assigning grammatical parts of speech tags to segmented words. The library allows for the training of custom segmentation models using annotated datasets and supports the integration of user-defined dictionaries to ensure specialized terminology is recognized correctly. It employs a multi-threaded execution engine to process large volumes of Ch
Employs a multi-threaded execution engine to process large volumes of Chinese text files in parallel.
该项目是一个综合性教育计划和深度学习框架,旨在通过 Notebook 和代码示例教授 PyTorch 深度学习实践。它作为一个用于构建、训练和部署神经网络的高级库,充当模型训练编排器,协调 PyTorch 模型、优化器和损失函数。 该项目为计算机视觉、自然语言处理和表格数据预处理提供了专门的工具包。它通过高级训练控制脱颖而出,例如判别式学习率、用于自定义训练逻辑的双向回调系统,以及自动化设备放置和训练循环的高级学习器抽象。 该框架涵盖了广泛的能力面,包括自动化数据流水线构建、模型架构分析以及跨分类、回归和分割任务的性能评估。它还包括用于跨多个 GPU 进行分布式训练的工具、用于内存优化的混合精度训练,以及对医学影像数据的专门支持。 该项目以一系列 Jupyter Notebook 的形式交付。
Distributes tokenization tasks across multiple CPU workers to accelerate processing of large text datasets.