Liquid AI 发布 LFM2.5-Encoder-230M 和 350M 双向编码器
Liquid AI Releases LFM2.5-Encoder-230M and LFM2.5-Encoder-350M: Bidirectional Encoders That Stay Fast at 8K Context on CPU
Liquid AI 新出的两个双向编码器，230M 在 CPU 上跑 8K 上下文只要 28 秒，350M 在 GLUE 等基准排第四，适合做嵌入和分类任务。
Liquid AI 推出了两个开源双向编码器 LFM2.5-Encoder-230M 和 LFM2.
5-Encoder-350M，均支持 8192 token 上下文窗口，基于 LFM2 混合主干架构。350M 版本在包含 17 个任务的 GLUE、SuperGLUE 和多语言基准测试中排名第四，仅落后于更大的模型。
230M 版本在 CPU 上完成一次 8K token 前向传播仅需约 28 秒。这两个模型专为 CPU 高效推理设计，保持快速处理长上下文。
Liquid AI Releases LFM2.5-Encoder-230M and LFM2.5-Encoder-350M: Bidirectional Encoders That Stay Fast at 8K Context on CPU
Liquid AI released two open-weight bidirectional encoders, LFM2.5-Encoder-230M and LFM2.5-Encoder-350M. Both carry an 8,192-token context and are built on the LFM2 hybrid backbone. The 350M ranks fourth of 14 models on a 17-task GLUE, SuperGLUE, and multilingual suite, behind only larger models. The 230M clears one 8K-token forward pass on CPU in about 28 seconds. The post Liquid AI Releases LFM2.5-Encoder-230M and LFM2.5-Encoder-350M: Bidirectional Encoders That Stay Fast at 8K Context on CPU appeared first on MarkTechPost .
This report is categorized under AITOP's "Models" desk. Key entities and technical topics under continuous tracking include LFM2.5-Encoder-230M, LFM2.5-Encoder-350M, Liquid AI, 双向编码器.
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