Nowadays, foundation models become one of fundamental infrastructures in artificial intelligence, paving ways to the general intelligence. However, the reality presents two urgent challenges: existing foundation models are dominated by the English-language community; users are often given limited resources and thus cannot always use foundation models. To support the development of the Chinese-language community, we introduce an open-source project, called Fengshenbang, which leads by the research center for Cognitive Computing and Natural Language (CCNL). Our project has comprehensive capabilities, including large pre-trained models, user-friendly APIs, benchmarks, datasets, and others. We wrap all these in three sub-projects: the Fengshenbang Model, the Fengshen Framework, and the Fengshen Benchmark. An open-source roadmap, Fengshenbang, aims to re-evaluate the open-source community of Chinese pre-trained large-scale models, prompting the development of the entire Chinese large-scale model community. We also want to build a user-centered open-source ecosystem to allow individuals to access the desired models to match their computing resources. Furthermore, we invite companies, colleges, and research institutions to collaborate with us to build the large-scale open-source model-based ecosystem. We hope that this project will be the foundation of Chinese cognitive intelligence.

翻译：当前，基础模型已成为人工智能领域的基础设施之一，为通用智能铺平道路。然而，现实存在两个紧迫挑战：现有基础模型主要由英语社区主导；用户通常仅拥有有限资源，因而无法始终使用基础模型。为支持中文社区的发展，我们介绍一个名为“封神榜”的开源项目，该项目由认知计算与自然语言研究中心（CCNL）主导。我们的项目具备全面能力，包括大型预训练模型、用户友好型应用程序接口、基准测试、数据集等。我们将这些内容整合为三个子项目：封神榜模型、封神框架和封神基准测试。“封神榜”开源路线图旨在重新评估中文预训练大规模模型的开源社区，推动整个中文大规模模型社区的发展。我们还希望构建以用户为中心的开源生态系统，使个人能够根据自身计算资源获取所需模型。此外，我们邀请企业、高校和研究机构与我们合作，共同构建基于大规模开源模型的生态系统。我们期待该项目将成为中文认知智能的基础。