OpenCodeInterpreter
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OpenCodeInterpreter is an open-source family of code-execution LLM systems that iteratively refine code using runtime feedback, closing the gap with GPT-4's proprietary Code Interpreter.
Code-Feedback dataset: Ships a 68K multi-turn training set that captures code-generation, execution results, and refinement steps - the key training ingredient for iterative code agents.
Execution + human loop: Integrates both automatic execution feedback and human-style critique signals, so the system learns to use runtime errors and natural-language feedback together.
HumanEval leaderboard: The 33B variant averages 83.2% on HumanEval/MBPP and reaches 91.6% with synthesized feedback - approaching GPT-4's 84.2% on the same evaluation.
Fully open: Code, data, and weights are released, giving the community a reproducible baseline for building iterative code agents.
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