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LFM2.5-Encoder-230M

LiquidAI · LFM2.5-Encoder-230M

**LFM2.5-Encoder** is a family of multilingual bidirectional encoders built on the LFM2 architecture, available in two sizes: Both are masked language models with full bidirectional attention, designed to be fine-tuned into task-specific models (classification, token classification, retrieval, reranking, and semantic similarity) across 15 languages, and to run efficiently on-device. > [!NOTE] > 💻 **Demos**: We built the demos below from fine-tuned LFM2.5-Encoders. Each one runs in a CPU-only Hugging Face space: > - **Zero-shot prompt routing** — define your own routing lanes as free text. The model scores the whole prompt against every lane in one pass. > - **Zero-shot policy linting** — check text against your company's rules, written as free text. It scores every token against every rule in one pass. > - **Spell checking** — correct misspellings token by token. > - **PII detection** — spot and remove 40 kinds of personal information across 16 languages. > - **Masked-diffusion text generation** — bonus: run the encoder as a chatbot that generates text by iteratively unmasking instead of left to right.

译文排队中,当前展示来源原文。

填空与掩码license:other
上下文窗口来源未披露
输入 → 输出文本 → 文本
模型权重待核验
档案更新时间2026/11/2 19:15:27
OVERVIEW

模型介绍

**LFM2.5-Encoder** is a family of multilingual bidirectional encoders built on the LFM2 architecture, available in two sizes: Both are masked language models with full bidirectional attention, designed to be fine-tuned into task-specific models (classification, token classification, retrieval, reranking, and semantic similarity) across 15 languages, and to run efficiently on-device. > [!NOTE] > 💻 **Demos**: We built the demos below from fine-tuned LFM2.5-Encoders. Each one runs in a CPU-only Hugging Face space: > - **Zero-shot prompt routing** — define your own routing lanes as free text. The model scores the whole prompt against every lane in one pass. > - **Zero-shot policy linting** — check text against your company's rules, written as free text. It scores every token against every rule in one pass. > - **Spell checking** — correct misspellings token by token. > - **PII detection** — spot and remove 40 kinds of personal information across 16 languages. > - **Masked-diffusion text generation** — bonus: run the encoder as a chatbot that generates text by iteratively unmasking instead of left to right.

主要特点

特点摘要待依据来源补齐,不凭模型名称推断能力。

局限与注意事项

暂无足够来源支持具体缺点结论。请重点验证实际任务表现、时延、数据政策、许可与版本生命周期。

PRICING & COST

来源报价与费用分析

同一模型在不同渠道、地区和配置下可能采用不同价格。下表独立保留各渠道报价,不将渠道价格视为厂商官方统一价格。

来源 / 渠道输入输出计费单位采集时间
暂未取得可核验报价,请查阅来源渠道。

按月估算基础 Token 费用

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预估不包含缓存优惠、阶梯定价、多模态附加费用、网络检索、税费及推理额外输出。

INDEPENDENT BENCHMARKS

公开评测与运行配置

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

查看完整已收录榜单 →

常见问题

开放权重是否代表可以免费商用?

不一定。应核对具体版本许可证、商用门槛和使用政策。自部署还会产生算力和维护成本。

这些价格是实时结算价格吗?

不是实时结算价格,而是带采集时间的来源报价快照。请到对应渠道核对当前版本、区域、折扣和计费方式。

资料来源与可追溯记录

许可证:other。模型介绍与第三方评测均以原来源的具体版本和方法为准。