InternLM/OREAL
Exploring the Limit of Outcome Reward for Learning Mathematical Reasoning
This project offers models specifically trained to solve complex mathematical reasoning problems. It takes mathematical problems as input and generates detailed, step-by-step solutions that lead to a correct final answer. Researchers and developers working on advanced AI systems that require strong mathematical problem-solving capabilities would use this.
193 stars. No commits in the last 6 months.
Use this if you are a researcher or AI developer aiming to enhance large language models' ability to accurately solve challenging math problems through advanced reinforcement learning techniques.
Not ideal if you are a non-technical user looking for a simple math problem solver or a developer without significant GPU resources and expertise in training large language models.
Stars
193
Forks
6
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 20, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/transformers/InternLM/OREAL"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
cvs-health/uqlm
UQLM: Uncertainty Quantification for Language Models, is a Python package for UQ-based LLM...
PRIME-RL/TTRL
[NeurIPS 2025] TTRL: Test-Time Reinforcement Learning
sapientinc/HRM
Hierarchical Reasoning Model Official Release
tigerchen52/query_level_uncertainty
query-level uncertainty in LLMs
reasoning-survey/Awesome-Reasoning-Foundation-Models
✨✨Latest Papers and Benchmarks in Reasoning with Foundation Models