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LiquidAI 发布 LFM2.5-Encoder，用于高效的设备端多语言任务

作者 PulseAugur 编辑部 · [1 个来源] ·

LiquidAI 发布了 LFM2.5-Encoder，这是一个多语言双向编码器模型，提供 2.5 亿和 3.5 亿参数两种尺寸。该模型基于 LFM 架构构建，专为高效的设备端性能而设计，包括通过 WebGPU 在网页浏览器中运行。它支持针对 15 种语言的各种任务进行微调，并且在其尺寸下表现强劲，可与其他编码器媲美，并优于该开发者之前的检索模型。 AI

影响 实现了高效的设备端多语言自然语言处理任务，可能提高了小型应用程序的可访问性。

排序理由 非前沿实验室发布新开源模型。[lever_c_research降级：ic=1 ai=1.0]

在 r/LocalLLaMA 阅读 →

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

LiquidAI 发布 LFM2.5-Encoder，用于高效的设备端多语言任务

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非前沿实验室发布新开源模型。[lever_c_research降级：ic=1 ai=1.0]
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报道来源 [1]

  1. r/LocalLLaMA TIER_1 (CA) · /u/jacek2023 ·

    LiquidAI/LFM2.5-Encoder 250M/350M

    <!-- SC_OFF --><div class="md"><p>LFM2.5-Encoder-350M is a multilingual bidirectional encoder built on the LFM2 architecture — a larger encoder for maximum downstream quality. It is a masked language model with full bidirectional attention, designed to be fine-tuned into task-spe…

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