Format Dataset For Llama 2 Instruction Prompts

What the source does

• FilesystemNone observedNo reads or writes in the source
• NetworkNone observedNo outbound calls in the source
• ShellNone observedNo commands run in the source
• DependenciesPinnedNothing floats
• SecretsNone foundNo keys in source

Five audit layers

Gates applied: no behavioural pass.

Audit 0.4.1 · source sha 04e912cff54b · 14 Oct 2026Report an issue or request a re-scan

• PublisherECNU-ICALK GitHub organizationOwner of the repository this skill is read from
• Source folderECNU-ICALK/AutoSkill/SkillBank/ConvSkill/english_gpt3.5_8_GLM4.7/format-dataset-for-llama-2-instruction-promptsThe exact folder we audited
• LicenceNot declaredAs the repository states it
• Commit pinned for this verdict04e912cff54bA new audit runs when the source changes
• Repository statusNot archivedLast push 157 days ago
• Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

Its description: Format the 'input' column of a dataset for Llama 2 instruction tuning by wrapping the content with specific start and end tags.

---
id: "d5298d8d-52a6-4223-8dee-0d5948acde25"
name: "Format Dataset for Llama 2 Instruction Prompts"
description: "Format the 'input' column of a dataset for Llama 2 instruction tuning by wrapping the content with specific start and end tags."
version: "0.1.0"
tags:
  - "dataset"
  - "llama-2"
  - "formatting"
  - "preprocessing"
  - "python"
triggers:
  - "format dataset for llama 2"
  - "add inst tags to dataset input"
  - "prepare dataset for llama 2 instruction tuning"
  - "wrap input with s inst tags"
---

# Format Dataset for Llama 2 Instruction Prompts

Format the 'input' column of a dataset for Llama 2 instruction tuning by wrapping the content with specific start and end tags.

## Prompt

# Role & Objective
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.

# Operational Rules & Constraints
1. Identify the target dataset and the specific split (e.g., 'train').
2. Locate the 'input' field within the dataset examples.
3. Prepend the string `<s><INST>` to the beginning of the existing 'input' content.
4. Append the string `</INST>` to the end of the existing 'input' content.
5. Update the dataset in place or create a new dataset with these modified values.

# Communication & Style Preferences
Provide Python code using the `datasets` library to perform this transformation efficiently.

# Anti-Patterns
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.

## Triggers

- format dataset for llama 2
- add inst tags to dataset input
- prepare dataset for llama 2 instruction tuning
- wrap input with s inst tags

Excerpt, first 1,797 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

git clone https://github.com/ECNU-ICALK/AutoSkill
git -C AutoSkill checkout 04e912cff54b

Works in

1. 2026-10-14
   ✓SAFE B 89 / 100

   first audit · source 04e912cff54b

Questions about Format Dataset For Llama 2 Instruction Prompts

• github.com/ECNU-ICALK/AutoSkill/tree/main/SkillBank/ConvSkill/en — the audited source at commit 04e912cff54b and every finding aboveObserved · 14 Oct 2026

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