At the Tencent Global Digital Ecology Conference on September 7, 2023,Tencent’s Hunyuan large model was officially unveiled and launched, and it was announced at the same time Open to the outside world through Tencent Cloud.
Tencent Hunyuan Large Model The features of include:
1. Strong language understanding ability
The Hunyuan large model has profound language understanding capabilities, can grasp complex language rules, and understand the meaning and logical relationships of natural language texts. Tencent's Hunyuan large model can understand the meaning of the context and has the ability to memorize long texts, allowing it to smoothly conduct multiple rounds of conversations in professional fields.
2. Multimodal knowledge understanding
The large Hunyuan model can integrate knowledge from multiple modalities, including text, images, voice, video, etc., to understand various information more comprehensively.
3. Efficient generation ability
The Hunyuan large model has efficient generation capabilities and can generate high-quality text, images, speech, etc., meeting the needs of a variety of application scenarios.
4. Multi-language support
The Hunyuan large model supports multiple languages, enables cross-language communication and translation, and enhances the ability of cross-border communication and cooperation.
Tencent conducts targeted research and development at the algorithm level to solve the "illusion" problem currently existing in large models.
Tencent fully embraces large models
In response to the problem that large models are prone to "gibberish", Tencent has optimized pre-training algorithms and strategies, reducing the illusion of Hunyuan large models by 30% to 50% compared with mainstream open source large models.
At the same time, through reinforcement learning methods, the model learns to identify trap questions and can refuse to answer inappropriate user questions; through position coding optimization, the processing effect and performance of very long texts are improved.
In addition, Tencent's R&D team also proposed a new strategy of thinking chain, which allows large models to reason and make decisions based on actual application scenarios like humans.
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