近日，OpenNLPLab 团队发布了一款名为 Lightning Attention-2 的新一代线性注意力机制，旨在一劳永逸地解决大语言模型长序列问题。该机制让长序列的训练和推理成本与 1K 序列长度的一致，使得在遇到显存瓶颈之前，无限增大序列长度不会对模型训练速度产生负面影响。这一突破使得无限长度预训练成为可能，并将极大地降低大语言模型的推理成本。
Lightning Attention-2 的提出，将有助于解决当前大语言模型在处理长序列时面临的挑战，进一步提高模型的性能和效率。这一创新技术有望在未来引领自然语言处理领域的新潮流，为推动人工智能技术的发展奠定坚实基础。
英文翻译：
News Title: New Generation Attention Mechanism Solves Long Sequence Problem
Keywords: OpenNLPLab, Lightning Attention-2, Large Language Models
News Content:
Recently, the OpenNLPLab team released a new generation of linear attention mechanism called Lightning Attention-2, which aims to solve the long sequence problem in large language models once and for all. This mechanism enables the training and inference cost of long sequences to be consistent with that of 1K sequences, allowing for no negative impact on model training speed before reaching the memory bottleneck. This breakthrough makes infinite-length pre-training possible and greatly reduces the inference cost of current large language models.
The introduction of Lightning Attention-2 will help address the challenges faced by large language models in processing long sequences, further enhancing the performance and efficiency of these models. This innovative technology is expected to lead the trend in the field of natural language processing and lay a solid foundation for the development of artificial intelligence technology.
【来源】https://www.jiqizhixin.com/articles/2024-01-18-5
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