An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model
Principalele funcționalități ale open-reasoner-zero/open-reasoner-zero sunt: Critic-Based Algorithms, Frontier Reasoning Models, Reasoning Datasets, Reasoning Models, Reinforcement Learning Frameworks.
Alternativele open-source pentru open-reasoner-zero/open-reasoner-zero includ: agentica-project/rllm — 🚀 Reinforcement Learning for Language Agents🌟. skyworkai/skywork-or1 — ✊ Unleashing the Power of Reinforcement Learning for Math and Code Reasoners 🤖. hiyouga/easyr1 — EasyR1 is a distributed model training system and reinforcement learning framework for large language and… deep-agent/r1-v. gair-nlp/limo — 📄 Paper | 🌐 Dataset (v2) | 📘 Model (v2). deepseek-ai/deepseek-r1 — DeepSeek-R1 is an open-weights large language model focused on advanced reasoning. It uses chain-of-thought processing…
✊ Unleashing the Power of Reinforcement Learning for Math and Code Reasoners 🤖
🚀 Reinforcement Learning for Language Agents🌟
DeepSeek-R1 is an open-weights large language model focused on advanced reasoning. It uses chain-of-thought processing and internal monologues to solve complex mathematical and logical problems by breaking tasks into sequential, verifiable thought processes. The model is developed using reinforcement learning to optimize reasoning patterns and verify logical steps. It employs a distillation process to transfer these high-performance logic capabilities from a large teacher model into smaller, computationally efficient versions. The training framework incorporates group relative policy optimiz