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Hunyuan-Large is Tencent’s recently open-sourced, large-scale Mixture of Experts (MoE) model, featuring 3.89 trillion total parameters and 52 billion active parameters.
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CogSound is a sound effects generation model developed by Zhipu Technology, designed to create sound effects that match the visual content of AI-generated videos. It integrates closely with the latest video generation model, CogVideoX v1.5, which has achieved significant improvements in video generation capabilities.
Hunyuan-Large is Tencent’s recently open-sourced, large-scale Mixture of Experts (MoE) model, featuring 3.89 trillion total parameters and 52 billion active parameters.
The Hunyuan-Large model currently offers three main versions:
Hunyuan-A52B-Pretrain: The pre-trained version, suitable for basic language understanding and generation tasks.
Hunyuan-A52B-Instruct: The instruction-tuned version, specifically trained to better respond to user prompts and task requirements.
Hunyuan-A52B-FP8: The FP8 version, optimized for specific hardware to improve inference efficiency and reduce memory usage.
Content Creation
Article and Story Generation: Hunyuan-Large can assist content creators in generating high-quality articles, stories, and poetry, offering writing inspiration and creative support.
Automated Writing: For automated generation of news articles, blogs, and social media content, Hunyuan-Large can quickly produce relevant text, improving writing efficiency.
Knowledge Q&A
Logical Reasoning and Mathematics
Logical Reasoning Tasks: Hunyuan-Large excels in tasks requiring common-sense understanding and reasoning, capable of handling complex logical reasoning problems.
Mathematical Problem Solving: The model performs well in mathematics, able to solve various math problems, which is beneficial for educational and research applications.
Programming and Code Generation
Long Text Processing
Multimodal Applications
Hunyuan-Large is Tencent’s latest open-source, large-scale Mixture of Experts (MoE) model, with 3.89 trillion total parameters and 52 billion active parameters. This model is the largest open-source Transformer-based MoE model to date, supporting up to 256K text sequence input, which significantly enhances its ability to handle tasks requiring long contexts.