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Multi-source AI news clustered, deduplicated, and scored 0–100 across authority, cluster strength, headline signal, and time decay.

TOOL · Mastodon — mastodon.social English(EN) · 5h

Liquid AI has released two new retrieval models for multilingual search across 11 languages. The LFM2.5-Embedding-350M dense bi-encoder and LFM2.5-ColBERT-350M

Liquid AI has launched two new retrieval models, LFM2.5-Embedding-350M and LFM2.5-ColBERT-350M, designed for efficient multilingual search in 11 languages. These models, each with 350 million parameters, are capable of running on edge devices. They are now accessible on the Hugging Face platform. AI

IMPACT Enables faster, more efficient multilingual search capabilities on edge devices.
SIGNIFICANT · r/LocalLLaMA (CY) · 1mo · [3 sources]

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

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.