Qwen2.5 is a suite of large language model foundation models designed for natural language generation, code production, and complex mathematical reasoning. The project encompasses a multilingual language model capable of processing dozens of languages and a specialized code generation model for technical problem solving and debugging. The framework is distinguished by its long context capabilities, enabling the analysis of massive inputs ranging from 256K up to 1 million tokens. It further functions as an agentic framework, utilizing standardized templates and parsers to execute autonomous wo
🚀 Reinforcement Learning for Language Agents🌟
Project Page For "Seg-Zero: Reasoning-Chain Guided Segmentation via Cognitive Reinforcement"
Principalele funcționalități ale dvlab-research/seg-zero sunt: Reasoning Models.
Alternativele open-source pentru dvlab-research/seg-zero includ: qwenlm/qwen2.5 — Qwen2.5 is a suite of large language model foundation models designed for natural language generation, code… agentica-project/deepscaler. agentica-project/rllm — 🚀 Reinforcement Learning for Language Agents🌟. aidc-ai/marco-o1 — An Open Large Reasoning Model for Real-World Solutions. aliyun/qwen-dianjin. adam-bjtu/openrft.