from src.display.utils import ModelType TITLE = """

OPEN-MOE-LLM-LEADERBOARD

""" INTRODUCTION_TEXT = """ The OPEN-MOE-LLM-LEADERBOARD is specifically designed to assess the performance and efficiency of various Mixture of Experts (MoE) Large Language Models (LLMs). This initiative, driven by the open-source community, aims to comprehensively evaluate these advanced MoE LLMs. We extend our gratitude to the Huggingface for the GPU community grant that supported the initial debugging process, and to [NetMind.AI](https://netmind.ai/home) for their generous GPU donation, which ensures the continuous operation of the Leaderboard. The OPEN-MOE-LLM-LEADERBOARD includes generation and multiple choice tasks to measure the performance and efficiency of MOE LLMs. Tasks: - **Generation Self-consistancy** -- [SelfCheckGPT](https://github.com/potsawee/selfcheckgpt) - **Multiple Choice Performance** -- [MMLU](https://arxiv.org/abs/2009.03300) Columns and Metrics: - Method: The MOE LLMs inference framework. - E2E(s): Average End to End generation time in seconds. - PRE(s): Prefilling Time of input prompt in seconds. - T/s: Tokens throughout per second. - Precision: The precison of used model. """ LLM_BENCHMARKS_TEXT = f""" """ LLM_BENCHMARKS_DETAILS = f""" """ FAQ_TEXT = """ --------------------------- # FAQ ## 1) Submitting a model XXX ## 2) Model results XXX ## 3) Editing a submission XXX """ EVALUATION_QUEUE_TEXT = """ """ CITATION_BUTTON_LABEL = "Copy the following snippet to cite these results" CITATION_BUTTON_TEXT = r""" """