Open Source Project

Open source AI model with 24 billion parameters featuring low-latency optimization and imperative task fine-tuning for conversational AI, low-latency automation, and domain-specific expertise applications.

An end-to-end testing framework based on natural language processing and AI technologies which streamlines the testing process, increases testing efficiency, and lowers the testing threshold.

Device-oriented open-source smart body framework designed to simplify the development of multimodal smart bodies and provide enhancements for various types of hardware devices.

A next-generation large-scale language modeling application development framework for easily building and operating generative AI native applications.

An open source digital human production platform designed to help users quickly create naturalistic digital human characters, dramatically reduce production costs and increase work efficiency.

An open source text-to-speech model optimized for conversational scenarios, capable of generating high-quality, natural and smooth conversational speech.

Python-based open source AI real-time face replacement tool that supports millisecond face replacement effects and can be used in a variety of fields such as entertainment, art creation and education.

Microsoft's open-source retrieval-enhanced generative model based on knowledge graph and graph machine learning techniques is designed to improve the understanding and reasoning of large language models when working with private data.

Open source software development agent platform designed to improve developer efficiency and productivity through features such as intelligent task execution and code optimization.

An open source framework for building large-scale language modeling application designs, providing modular components and toolchains to support the entire application lifecycle from development to production.

Multi-intelligent body collaboration open source framework, through the simulation of software company operation process, to achieve efficient collaboration and automation of GPT model in complex tasks.

AI face swap open source project that uses deep learning techniques to achieve high quality face replacement and image processing .

Open source sound cloning tool focused on enabling high quality, cross-language sound (especially singing) conversion.

Open source chat application tool that allows users to query and access relevant information in documents by chatting.

Based on the GPT-4 open-source project, integrating Internet search, memory management, text generation and file storage, etc., it aims to provide a powerful digital assistant to simplify the process of user interaction with the language model.

Huawei's full-scenario deep learning framework is designed to provide full-stack AI capabilities that are easy to develop and efficient to execute, supporting the complete process from data loading and model building to training, evaluation and deployment.

An open source AI engineering optimization platform focused on AI engineering from first principles. It helps users collect, understand and use data to improve the quality of LLM (Large Language Model) applications.

Unified image generation diffusion model, which naturally supports multiple image generation tasks with high flexibility and scalability.

The AI model, which is open-source under the MIT License, has advanced reasoning capabilities and supports model distillation. Its performance is benchmarked against OpenAI o1 official version and has performed well in multi task testing.

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.