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Knowledge Benchmarking Overview

The Knowledge Benchmark module in the Open Innovation Platform enables precise evaluation of large language models (LLMs). With access to more than 2,000 predefined benchmarks and the ability to create custom assessments, you can measure model performance across diverse tasks and metrics.

Key Features

  1. Extensive Benchmark Library

    • Choose from a wide range of benchmark packages targeting various tasks and metrics.
    • Tailor your testing approach by selecting only the benchmarks relevant to your specific requirements.

  2. Custom Benchmark Creation

    • Design benchmarks aligned with your organization’s unique goals.
    • Specify task descriptions, evaluation metrics, and any specialized requirements.

  3. Benchmark Runs

    • Launch tests by selecting the target model and allocating resources.
    • Optimize computational overhead for accurate and efficient performance measurements.

  4. Comparison & Analysis

    • Compare multiple benchmark runs to identify performance variations.
    • Gain insights into model efficiency and effectiveness under different settings.

  5. Prompt Files Management

    • Manage and modify prompt files used in benchmarks.
    • Keep tests up to date with model capabilities and evolving evaluation needs.

  6. Few-Shot Learning Configuration

    • Incorporate few-shot examples into benchmark prompts.
    • Adjust the number of examples to enhance benchmark accuracy and relevance.

Next Steps

  • LLM Fine-Tuning UI – Learn how to adapt models for specialized tasks before benchmarking.
  • Inference UI – Deploy and test LLM performance interactively.
  • LoRA Adapters – Discover how to efficiently fine-tune LLMs by updating only a small set of parameters.