yongchao98/R1-Code-Interpreter
R1-Code-Interpreter: Training LLMs to Reason with Code via Supervised and Reinforcement Learning
This project helps AI researchers and developers train Large Language Models (LLMs) to perform complex reasoning tasks by autonomously generating and executing code. It provides a framework and pre-trained models that take a reasoning or planning problem as input and output a step-by-step solution, potentially involving code execution for self-correction. The ideal user is an AI model developer or researcher looking to enhance LLMs' ability to reason and solve problems programmatically.
Use this if you are an AI researcher or developer aiming to improve an LLM's capacity for multi-step reasoning and problem-solving through code generation and execution.
Not ideal if you are an end-user without deep machine learning expertise simply looking for an off-the-shelf tool to solve a specific business problem.
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Language
Python
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Last pushed
Feb 09, 2026
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