信创模盒ModelHub XC｜模型适配认证2000+ 补齐推理代码等关键能力类型

Core Insights - The core point of the news is the significant progress made by Fan Shi Intelligent in the development of the ModelHub XC, which has surpassed 2000 certified models ahead of schedule, enhancing the adaptability and efficiency of AI models on domestic computing platforms [1][2]. Group 1: ModelHub XC Progress - The ModelHub XC has achieved over 2000 certified models, exceeding the expected timeline by half a month [1]. - The platform has accelerated its computational engine's automated adaptation capabilities, improving both the speed and quality of model adaptation [1]. - The certification of models comes from contributions by over 100 open-source organizations and developer communities, covering mainstream open-source systems such as Qwen, Llama, Mistral, Phi, and DeepSeek [1]. Group 2: Adaptation and Integration - The adaptation primarily focuses on domestic computing platforms like Ascend 910B3/910B4, while also expanding to platforms such as Mu Xi Xi Cloud C500, Haiguang K100AI, and Tian Shu Zhi Xin Zhi Kai 100 [1]. - The ModelHub XC facilitates a tagged matching of models, hardware, and software, helping developers reduce trial and error [1]. - The platform offers value-added services for self-developed or complex industry models, optimizing the final adjustments and lowering the costs and deployment barriers for AI in critical infrastructure sectors [1]. Group 3: Industry Collaboration - The rapid adaptation of ModelHub XC is crucial for achieving a self-controlled AI industry in China, transitioning from merely running large models to running them efficiently on domestic computing [2]. - The company invites developers, enterprises, and industry partners to join the ModelHub ecosystem for collaborative model adaptation, technical optimization, and scenario co-construction [2]. Group 4: About ModelHub XC - ModelHub XC is an AI model and tool platform aimed at the domestic computing ecosystem, providing a comprehensive solution from model training and inference to deployment [3].