Unverified50% confidenceFactExact time
GPT-3 的预训练语料以自然语言为主，代码仅占约 1%，而 Codex 的微调数据集中代码占比超过 90%
1
Sources
50%
Confidence
Long-term
Relevance
7/6/2026
First Seen
Sources
Codex CLI Practical Guide: From Setup to Enterprise-Level AI Development
bilibiliAI大模型技术教程7/3/2026
Related Claims
UnverifiedThe early GPT-3 model demonstrated some code comprehension ability, but its training data was primarily natural language, limiting the accuracy and engineering practicality of its code generation.80% similarUnverifiedCodex was fine-tuned on top of GPT-3 using approximately 154 billion tokens of publicly available code repository data covering 54 programming languages, achieving a pass@1 accuracy of 28.8% on the HumanEval benchmark, compared to 0% for GPT-3 at the same time.75% similarVerifiedModern large language models such as GPT-4, Claude 3, and Gemini, having been pre-trained on massive code corpora, are already capable of understanding natural language descriptions and generating high-quality, runnable code.73% similarUnverified谷歌DeepMind的研究发现GPT类模型在特定提示条件下可精确复现训练集中约1%的文本片段72% similar
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