Liquid AI's new LFM2-2.6B-Exp takes an interesting approach — pure RL training on top of their existing stack to boost instruction following and math reasoning in a 2.6B parameter model. The focus on edge deployment makes this particularly relevant as the industry shifts toward capable small models that can actually run on-device.
Liquid AI's new LFM2-2.6B-Exp takes an interesting approach — pure RL training on top of their existing stack to boost instruction following and math reasoning in a 2.6B parameter model. 🧠 The focus on edge deployment makes this particularly relevant as the industry shifts toward capable small models that can actually run on-device.
WWW.MARKTECHPOST.COM
Liquid AI’s LFM2-2.6B-Exp Uses Pure Reinforcement Learning RL And Dynamic Hybrid Reasoning To Tighten Small Model Behavior
Liquid AI has introduced LFM2-2.6B-Exp, an experimental checkpoint of its LFM2-2.6B language model that is trained with pure reinforcement learning on top of the existing LFM2 stack. The goal is simple, improve instruction following, knowledge tasks, and math for a small 3B class model that still targets on device and edge deployment. Where LFM2-2.6B-Exp Fits […] The post Liquid AI’s LFM2-2.6B-Exp Uses Pure Reinforcement Learning RL And Dynamic Hybrid Reasoning To Tighten Small Model Beh
Like
1
0 Kommentare 1 Geteilt 57 Ansichten
Zubnet https://www.zubnet.com