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llm-psicotest: New tool evaluates LLM behavior after quantization

By PulseAugur Editorial · [1 sources] ·

A new tool called llm-psicotest has been released to evaluate the behavior of large language models, particularly after quantization. This seeded, 38-turn conversation benchmark tests model capabilities and consistency over extended interactions. The tool uses byte-identical prompts and code-based scoring to assess performance, aiming to provide more robust evaluations than multiple-choice benchmarks. AI

IMPACT Provides a new method for evaluating LLM consistency and behavior changes after quantization.

RANK_REASON The cluster describes a new software tool for evaluating LLMs.

Read on r/LocalLLaMA →

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

llm-psicotest: New tool evaluates LLM behavior after quantization

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4 / 100
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The cluster describes a new software tool for evaluating LLMs.
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High
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Breaking (< 6h)
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COVERAGE [1]

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

    llm-psicotest: a seeded 38-turn conversation to check whether a quant swap changed behaviour

    <!-- SC_OFF --><div class="md"><p>llm-psicotest runs one 38-turn conversation against any OpenAI-compatible endpoint: 29 capability items plus protocol turns. The items come from seeded generators, so a seed gives byte-identical prompts on any machine, and code scores every turn …

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