Fine-tuned version of LiquidAI/LFM3-1.7B aligned with Direct Preference Optimization (DPO) to eliminate hallucinations in Retrieval-Augmented Generation (RAG) pipelines. Small language models (< 3B) often fail to admit when retrieved documents do not con
AGI-0 Labs' Reflection Model : A model created by agi0labs based on mattshumer/Reflection-Llama-3.1-70B, offering similar results in language understanding and generation tasks.
LFM2.5-2.6B by Liquid AI — deploy agents everywhere. A 2.6B dense reasoning model (Q4_K_M, ~1.7 GB) with native tool calling, 128K context, and 16-language support. Runs on any 8 GB GPU.