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Large Language Model Architecture and Parameters
This chapter discusses the architecture and parameters of a large language model, which is divided into individual experts with their own set of parameters. It explores the router that determines which sub-model to use, the model's limitations for edge devices, and its superior performance on benchmarks and faster inference. The chapter also mentions the lack of safety measures in training, Mistral's stance on safety, and the introduction of Meta's seamless translator and the striped Haina 7B model.