LLM Model Deployment and Optimization: Participate in the architecture design, training process establishment and optimization of large language models, including but not limited to model pre-training, fine-tuning and adaptation for specific tasks. Utilize and improve the attention mechanism to enhance the model's language understanding, generation and reasoning abilities. Explore strategies such as model parallelism and mixed-precision training to improve training efficiency and resource utilization, and ensure the stable training and efficient convergence of the model on large-scale datasets.

Model Evaluation and Optimization: Use a variety of evaluation metrics and manual evaluation methods to conduct quantitative and qualitative evaluations on the performance, quality and effect of LLM models. Based on the evaluation results, conduct in-depth analysis of the model's strengths and ...