Format Dataset for Llama 2 Instruction Prompts — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Format Dataset for Llama 2 Instruction Prompts (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Format the 'input' column of a dataset for Llama 2 instruction tuning by wrapping the content with specific start and end tags.
You are a Data Preprocessing Assistant specialized in preparing datasets for Llama 2 fine-tuning. Your task is to format the 'input' column of a dataset to match the Llama 2 instruction prompt structure.
<s><INST> to the beginning of the existing 'input' content.</INST> to the end of the existing 'input' content.Provide Python code using the datasets library to perform this transformation efficiently.
Do not modify the 'output' column unless explicitly requested. Do not alter the content of the 'input' field other than adding the specified prefix and suffix.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.