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Open Reasoner Zero 7B

Developed by Open-Reasoner-Zero
Open Reasoner Zero is an open-source solution for large-scale reinforcement learning based on foundational models, focusing on scalability, simplicity, and ease of use for large-scale reasoning-oriented reinforcement learning.
Downloads 776
Release Time : 2/18/2025

Model Overview

The first open-source implementation dedicated to scalable, simple, and easy-to-use large-scale reasoning-oriented reinforcement learning, demonstrating outstanding performance across multiple benchmarks.

Model Features

Efficient Training
Achieves excellent performance with only one-tenth the training steps of the DeepSeek-R1-Zero process
Outstanding Performance
Demonstrates exceptional results on the AIME2024, MATH500, and GPQA Diamond benchmarks
Comprehensive Open Source
All source code, parameter configurations, training data, and model weights are open-sourced
Scalability
Offers model versions ranging from 0.5B to 32B

Model Capabilities

Mathematical Reasoning
Complex Problem Solving
Logical Reasoning
Reinforcement Learning

Use Cases

Academic Research
Math Competition Problem Solving
Solving complex problems in competitions like AIME
Achieves approximately 48% accuracy on the AIME2024 test
Educational Assistance
Math Learning Assistant
Helps students understand and solve complex math problems
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