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English(EN) Tessera-27B-B-CJK, Zellige AIs new finetune of Qwen with novel approaches to how we think about token savings

Zellige AI发布Tessera-27B-B-CJK,一个用于代币效率的Qwen微调模型

Zellige AI发布了Tessera-27B-B-CJK,这是Qwen3.8-27B模型的一个新微调版本。该模型专为代理循环设计,并采用了一种新颖的压缩CJK(中文、日文、韩文)字符思考方法,以显著减少每个回合的代币使用量。虽然基础Qwen模型在编码任务上平均每个回合花费137个代币,但Tessera-27B-B-CJK通常使用该数量的0.50倍到0.64倍。该模型保持有效的工具调用并避免重复循环,并且在超过100K代币的提示上表现出鲁棒性。 AI

影响 该模型在代币压缩方面的方法可能带来更高效的AI代理和更低的运营成本。

排序理由 发布了一个具有新颖效率技术微调的开放权重模型。[lever_c_demoted from research: ic=1 ai=1.0]

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AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

Zellige AI发布Tessera-27B-B-CJK,一个用于代币效率的Qwen微调模型

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发布了一个具有新颖效率技术微调的开放权重模型。[lever_c_demoted from research: ic=1 ai=1.0]
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model release, product
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完整方法见我们的编辑标准。

报道来源 [1]

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

    Tessera-27B-B-CJK,Zellige AI 对 Qwen 的新微调,采用新颖的方法来思考 token 节省问题

    <table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1x5xm28/tessera27bbcjk_zellige_ais_new_finetune_of_qwen/"> <img alt="Tessera-27B-B-CJK, Zellige AIs new finetune of Qwen with novel approaches to how we think about token savings" src="https://preview.redd.it/…