InstructEval Leaderboard

InstructEval
Leaderboard

Instructed language models (ILMs) play a crucial role in natural language processing, generating text that aligns with specific prompts or instructions and serving as a versatile tool for diverse applications.

Problem: Evaluating instructed language models presents challenges due to the abundance of available models in the market. The scattered nature of relevant information across various online sources further complicates the evaluation process.

Solution: To address this, we have developed the instructeval leaderboard—a solution designed to assist researchers in identifying outstanding instructed language models. These rankings facilitate informed decision-making in selecting the most suitable instructed language models.

View Models
RankModelSizeArchitectureOrganizationScore
A weighted average of the adoption and capability score of the model.
#1FLAN-UL2100BT5Google AI51.6
#2Alpaca Lora65BTransformer-XLStanford University50
#3Open Assistant30BSwitch TransformerLAION46.5
#4StableVicuna13BLLaMA TransformerStabilityAI40.9
#5Guanaco65BInstruction-following LanguageUW NLP group39.2
#6OPT-IML30BOPTMeta AI38.7
#7ChatGLM6BTransformerTsinghua University33.2
#8Falcon-7b-instruct7BCausal Decoder-onlyTII22.2
#9TK-Instruct11BEncoder and DecoderAllen Institute for Artificial Intelligence (AI2)26.8

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This whitepaper will explore generative AI and identify business growth opportunities it offers. We aim to provide business owners with a comprehensive guide to using AI to unlock new opportunities and achieve sustainable growth. We will explore how generative AI can be used to analyze data and identify patterns, as well as how it can be used to generate new ideas and solutions.

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