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Mistral Small 3 24B excels at emulating human text in reversed chat template tests

By PulseAugur Editorial · [1 sources] ·

An experiment explored how well instruction-tuned large language models can generate human-like text when prompted to act as the user. The study found that using reversed chat templates, where models generate the user's turn, was more effective than role-playing system prompts. Among the approximately 30 models tested, Mistral Small 3 24B performed best at emulating human behavior in this manner. AI

IMPACT This research suggests a new method for evaluating and potentially improving LLM's ability to generate natural, human-like dialogue.

RANK_REASON Research into LLM behavior using a novel method. [lever_c_demoted from research: ic=1 ai=1.0]

Read on r/LocalLLaMA →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Mistral Small 3 24B excels at emulating human text in reversed chat template tests

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Research into LLM behavior using a novel method. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/EntropyMagnets ·

    I tried reversing chat templates to see which models are the best at generating user turns

    <!-- SC_OFF --><div class="md"><p>I tried for fun to see what happens if we let instruction-tuned LLMs generate the text that should come from the user (so after the <code>user_start</code> special token). I immediately noticed that some models were way better than others.</p> <p…

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