The correct option is Private code stored in Cloud Source Repositories that belongs to your company.

Training a code assistance model on internal proprietary repositories risks exposing confidential or regulated information and it can violate internal data governance policies because you would be repurposing code that was created for internal use without an explicit data use consent. Excluding Private code stored in Cloud Source Repositories that belongs to your company helps prevent leakage of secrets and trade secrets and aligns with privacy and ethical compliance requirements for enterprise AI workloads on Vertex AI.

Although Private code stored in Cloud Source Repositories that belongs to your company references Google Cloud Source Repositories, which has been retired, the principle remains the same on newer exams and in real projects. You should not include any private company repositories in model training datasets unless you have a clear legal basis and documented consent that covers model training and distribution.

Q and A snippets published under Creative Commons licenses on community sites are generally acceptable for training if the chosen Creative Commons license permits reuse for the intended purpose and you meet attribution and other conditions that the license requires.

Open source projects mirrored on non GitHub platforms like mcnz.com are not excluded by default because the key factor is the open source license and your compliance with its terms. You must verify that the mirror is legitimate and that you honor the license obligations, yet the mere fact that the host is not GitHub does not make it unsuitable.

Public code with permissive licenses such as Apache 2.0 or MIT is typically suitable for training because these licenses allow broad reuse. You still need to comply with requirements such as preserving license notices and attribution where required, but permissive licensing does not necessitate exclusion from the dataset.

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