# Chinese

Data-Juicer is a comprehensive multimodal data processing system aimed at delivering higher quality, richer, and more digestible data for large language models (LLMs). It offers a systematic and reusable data processing library, supports collaborative development between data and models, allows rapid iteration through a sandbox lab, and provides features like data and model feedback loops, visualization, and multidimensional automated evaluation, helping users better understand and improve their data and models. Data-Juicer is actively maintained and regularly enhanced with more features, data recipes, and datasets.

llama3-Chinese-chat is the first Chinese conversational version of llama3, designed specifically for Chinese users, supporting high-quality multi-turn dialogue. It has been trained on 170k+ Chinese conversation data and possesses features such as role-playing and agent ability enhancement. Detailed training and inference tutorials are also provided. Furthermore, the project plans to open-source a browser extension, adding AI note-taking and mind mapping functionalities to further enhance user experience.

Chinese Tiny LLM (CT-LLM) is the first large language model designed specifically for Chinese. It boasts 2 billion parameters and has been pre-trained on a 120 billion Chinese text corpus. CT-LLM prioritizes enhancing the understanding and generation of the Chinese language. Through pre-training on massive Chinese data, it achieves efficient processing of Chinese text. While optimized for Chinese processing, CT-LLM also demonstrates proficiency in handling English and programming code, showcasing the model's cross-lingual adaptability. In the Chinese language benchmark CHC-Bench, CT-LLM exhibits outstanding performance, proving its efficiency in understanding and applying Chinese. CT-LLM is trained from scratch, primarily using Chinese data for pre-training. It openly shares all relevant information, including the entire data filtering process, training dynamics, training and evaluation data, and intermediate model checkpoints. This open-source approach allows other researchers and developers to access these resources, leveraging them for their own research or further model refinement.

EmotiVoice is a powerful and modern open-source text-to-speech engine. It supports both English and Chinese and boasts over 2000 distinct voices. Its most notable feature is emotion synthesis, allowing you to create voices with a range of emotions, including joy, excitement, sadness, anger, and more. EmotiVoice offers an easy-to-use web interface as well as a scripting interface for batch result generation. Key features include: 1. Support for English and Chinese 2. Over 2000 diverse voices 3. Emotion synthesis functionality Price: Free Target audience: Developers and researchers.