LiquidAI/Embeddings
Liquid AI's LFM2.5 encoder targets fast CPU inference
A 230M-parameter bidirectional encoder built for long-context English and German embeddings without a GPU.
Company
Releases
A 230M-parameter bidirectional encoder built for long-context English and German embeddings without a GPU.
The compact LFM2.5 encoder targets fast, long-context text embeddings without a GPU.
A 230-million-parameter multilingual model built to run efficiently at the edge rather than in the cloud.
LFM2.5-Embedding-350M targets retrieval and search workloads on edge hardware, where compact size matters as much as accuracy.