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LMMS-EVAL: A Unified and Standardized Multimodal AI Benchmark Framework
Fundamental Large Language Models (LLMs) like GPT-4, Gemini, and Claude have shown remarkable capabilities, rivaling or surpassing human performance. To address the need for transparent and reproducible evaluations of language and multimodal models, the LMMS-EVAL suite has been developed.
LMMS-EVAL evaluates over ten models with over 30 sub-variants across more than 50 tasks, ensuring impartial and consistent comparisons. It offers a standardized assessment pipeline to guarantee openness and repeatability.
LMMS-EVAL LITE: Affordable and Comprehensive Evaluation
LMMS-EVAL LITE provides a cost-effective and thorough evaluation by focusing on a variety of tasks and eliminating unnecessary data instances. It offers dependable and consistent results while reducing expenses, making it an affordable substitute for in-depth model evaluations.
LIVEBENCH: Benchmarking Zero-Shot Generalization Ability
LIVEBENCH evaluates models’ zero-shot generalization ability on current events by using up-to-date data from news and forum websites. It offers an affordable and broadly applicable approach to assess multimodal models, ensuring their continued applicability and precision in real-world situations.
Unlock the Power of AI for Your Business
AI benchmarks are crucial for distinguishing between models, identifying flaws, and guiding future advancements. LMMS-EVAL, LMMS-EVAL LITE, and LiveBench are designed to close gaps in assessment frameworks and facilitate the continuous development of AI.
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