清华大学开源CodeGeeX4-ALL-9B：多语言代码生成模型 超越主要竞争对手
清华大学知识工程组与数据挖掘团队新推出CodeGeeX4-ALL-9B，作为CodeGeeX系列的最新成果，其在多语言代码生成领域达到巅峰，重新定义自动化编码性能与效率标准。基于GLM-4-9B框架，经过广泛训练的它拥有9.4亿参数，超越同类模型，擅长代码生成、补全与解释，展现优异推理速度与整体性能。适应能力极强，涵盖了软件开发全方面需求，提供仓库级别的代码问答功能，助力开发者与代码库交互更为直观高效。基准测试显示在BigCodeBench和NaturalCodeBench上的优越表现，确认了其在真实应用中强大的可靠性和创新能力。以用户为中心的设计使其易于集成各种版本的transformers库，兼容GPU与CPU，确保不同计算环境的灵活性与广泛性采用。CodeGeeX4-ALL-9B可通过其推理过程，根据用户输入生成精准、可操作的代码输出，优化开发流程，尤其对于复杂算法和自动化编码任务极具价值。这一利器标志着代码生成领域的重要进步，将极大地提升软件开发的效率与创新。
%20--%3e%3cdefs%3e%3cstyle%3e%20.st0%20{%20fill:%20%23061b40;%20}%20.st1%20{%20fill:%20%23306af1;%20}%20.st2%20{%20fill:%20%235ce5cf;%20}%20%3c/style%3e%3c/defs%3e%3cg%3e%3cpath%20class='st0'%20d='M55,10.5h9v3h-9v9h12V7.5h-12v3ZM64,19.5h-6v-3h6v3Z'/%3e%3cpolygon%20class='st0'%20points='69%2016.5%2078%2016.5%2078%2019.5%2069%2019.5%2069%2022.5%2081%2022.5%2081%2013.5%2072%2013.5%2072%2010.5%2081%2010.5%2081%207.5%2069%207.5%2069%2016.5'/%3e%3cpolygon%20class='st0'%20points='95%2010.5%2095%207.5%2083%207.5%2083%2022.5%2095%2022.5%2095%2019.5%2086%2019.5%2086%2016.5%2095%2016.5%2095%2013.5%2086%2013.5%2086%2010.5%2095%2010.5'/%3e%3cpath%20class='st0'%20d='M40,1.5v21h11.6l1.4-1.4v-7.6h0c0,0-1.4-1.5-1.4-1.5l1.4-1.4V2.9l-1.4-1.4h-11.6ZM50,19.5h-7v-6h7v6ZM50,10.5h-7v-6h7v6Z'/%3e%3c/g%3e%3cpath%20class='st1'%20d='M23.1,24L14.7,4.8l-4.9,11.2h3.8l-1.8,4H3.3L12.1,0H2C.9,0,0,.9,0,2v20c0,1.1.9,2,2,2h21.1Z'/%3e%3cpath%20class='st2'%20d='M34,0h-16.8l10.6,24h6.2c1.1,0,2-.9,2-2V2C36,.9,35.1,0,34,0ZM32.5,20h-4V4h4v16Z'/%3e%3c/svg%3e)
