Open Source Project

Beijing Zhiyuan Artificial Intelligence Research Institute launched a large model containing several series with large-scale, high-precision, emergent and universal characteristics, and has been fully open-sourced.

Racer has open-sourced a text-to-image generation model called Kolors (Kotu), which has a deep understanding of English and Chinese and is capable of generating high-quality, photorealistic images.

The 7 billion parameter semantic grand model based on the Transformer architecture launched by China Telecom has powerful natural language understanding and generation capabilities, and is applicable to multiple AI application scenarios such as intelligent dialog and text generation.

Shanghai AI Lab leads the launch of a comprehensive big model research and development platform, providing an efficient tool chain and rich application scenarios to support multimodal data processing and analysis.

Developed by Kunlun World Wide Web, the open source big model, with 13 billion parameters and 3.2 trillion high-quality multi-language training data, has demonstrated excellent natural language processing capabilities in Chinese and other languages, especially in the Chinese environment, and is applicable to a number of domains.

An open source generative language model developed by Tsinghua University, designed for Chinese chat and dialog tasks, demonstrating powerful Chinese natural language processing capabilities.

A powerful large-scale language model with about 7.3 billion parameters, developed by Mistral.AI, demonstrates excellent multilingual processing power and reasoning performance.

Google's lightweight, state-of-the-art open-source models, including Gemma 2B and Gemma 7B scales, each available in pre-trained and instruction-fine-tuned versions, are designed to support developer innovation, foster collaboration, and lead to responsible use of the models through their powerful language understanding and generation capabilities.

xAI released an open source large language model based on hybrid expert system technology with 314 billion parameters designed to provide powerful language understanding and generation capabilities to help humans acquire knowledge and information.

Developed by Google, the pre-trained language model based on the Transformer architecture provides a powerful foundation for a wide range of NLP tasks by learning bi-directional contextual information on large-scale textual data with up to tens of billions of parameters, and has achieved significant performance gains across multiple tasks.

A large open-source multilingual language model developed by over 1,000 researchers from more than 60 countries and 250 institutions, with 176B parameters and trained on the ROOTS corpus, supporting 46 natural languages and 13 programming languages, aims to advance the research and use of large-scale language models by academics and small companies.

Alibaba launched a large-scale language model with multiple parameter scales from 0.5B to 72B, supporting multilingual processing, long text comprehension, and excelling in several benchmark tests.

A high-performance large-scale language model from Microsoft, tuned with instructions to support cross-platform operation, with excellent language comprehension and reasoning capabilities, especially suitable for multimodal application scenarios.

Meta's high-performance open-source large language model, with powerful multilingual processing capabilities and a wide range of application prospects, especially in the conversation class of applications excel.