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LiquidAI releases LFM2.5 embedding and ColBERT retrieval models

By PulseAugur Editorial · [3 sources] ·

LiquidAI has released two new multilingual retrieval models: LFM2.5-Embedding-350M, a dense bi-encoder for fast indexing, and LFM2.5-ColBERT-350M, a late-interaction model for higher accuracy. Both models have 350 million parameters, support 11 languages, and are designed to be drop-in replacements for existing RAG pipelines, offering efficient and reliable cross-lingual search capabilities. AI

IMPACT These models offer efficient and accurate multilingual retrieval, potentially improving RAG pipelines for cross-lingual search applications.

RANK_REASON New model release from a notable AI lab. [lever_c_demoted from frontier_release: ic=2 ai=1.0]

Read on r/LocalLLaMA →

AI-generated summary · Google Gemini · from 3 sources. How we write summaries →

LiquidAI releases LFM2.5 embedding and ColBERT retrieval models

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Significant
New model release from a notable AI lab. [lever_c_demoted from frontier_release: ic=2 ai=1.0]
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3 independent sources
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model release, product
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High
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144 days old
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Full methodology in our editorial standards.

COVERAGE [3]

  1. Hugging Face Trending Models TIER_1 Français(FR) · LiquidAI ·

    LiquidAI/LFM2.5-ColBERT-350M

    sentence-similarity · 103 downloads · 50 likes

  2. Hugging Face Trending Models TIER_1 English(EN) · LiquidAI ·

    LiquidAI/LFM2.5-Embedding-350M

    sentence-similarity · 3,734 downloads · 50 likes

  3. r/LocalLLaMA TIER_1 (CY) · /u/pmttyji ·

    LFM2.5-Embedding-350M & LFM2.5-ColBERT-350M

    <table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1u9ddft/lfm25embedding350m_lfm25colbert350m/"> <img alt="LFM2.5-Embedding-350M &amp; LFM2.5-ColBERT-350M" src="https://preview.redd.it/ensz6vvpw28h1.jpeg?width=640&amp;crop=smart&amp;auto=webp&amp;s=f94647a90a…

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