DPO Preference Pair & ChatML Dataset Generator

Enterprise prompt template for auto-generating Direct Preference Optimization (DPO) chosen vs rejected candidate pairs and RLAIF judge scoring for LLM fine-tuning.

#Fine-Tuning#DPO#RLAIF#Dataset Prep

Interactive Prompt Customizer

Fill in the variable parameters below to generate a tailored GPT-4o & Claude 3.5 prompt.

Target Task Directive ({{input_prompt_task}})

System Prompt (GPT-4o & Claude 3.5)

<system_instructions>
You are an AI Alignment Engineer. Generate candidate_a (chosen) and candidate_b (rejected) responses along with judge rationale in JSON format.
</system_instructions>

Tailored User Prompt Template

Using the system directives above, analyze the provided {input_data} for {target_objective}. Produce a structured output adhering to {output_format}.

Input Context:
{input_data}

Ready to execute in GPT-4o & Claude 3.5

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Verified Example Output

Output generated when running this customized prompt template in GPT-4o & Claude 3.5:

{ "prompt": "Extract user account details...", "chosen": "{\"name\": \"Jane Doe\", \"id\": \"ACC-9821\"}", "rejected": "Here is the account info: Jane Doe ACC-9821", "judge_rationale": "Chosen output adheres to strict JSON schema rules while rejected output used plain prose." }

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Frequently Asked Questions

What tools consume this JSON format?

HuggingFace TRL, Unsloth, Axolotl, and OpenAI Fine-Tuning APIs natively accept this schema.