#Linear Attention

TransNormerLLM's linear attention architecture offers improved accuracy and efficiency compared to traditional methods. Utilizing a corpus of 1.4 trillion tokens, it allows experimentation in various languages and domains. The open-source model provides weights and extensive fine-tuning options for academic use, with available base versions of 385M, 1B, and 7B parameters. Continuing development suggests expanding capabilities, highlighting its significant impact on AI evolution.