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New DeepSWE-mini dataset offers faster model benchmarking

By PulseAugur Editorial · [1 sources] ·

A new, more efficient dataset called DeepSWE-mini has been released, designed to replicate the ranking performance of the full DeepSWE benchmark. This subset consists of 16 instances and allows for quicker local testing and benchmarking of models. The goal is to provide a faster method for evaluating new models while maintaining the relative performance rankings found in the larger benchmark. AI

IMPACT Enables faster and more efficient local evaluation of language models.

RANK_REASON The cluster describes a new dataset for benchmarking, which falls under research. [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 →

New DeepSWE-mini dataset offers faster model benchmarking

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7 / 100
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The cluster describes a new dataset for benchmarking, which falls under research. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

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

    DeepSWE-mini a 16 instance subset of DeepSWE that replicates the rankings of the leaderboard

    <!-- SC_OFF --><div class="md"><p>I just released a new dataset <a href="https://huggingface.co/datasets/LocalLLaMA/deepswe-mini">https://huggingface.co/datasets/LocalLLaMA/deepswe-mini</a> it is meant to be more efficent when testing and benchmarking local models on DeepSwe <a h…

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