Fine-Tune Dataset Card
Dataset Overview
This dataset is designed for fine-tuning Mistral-7B-Instruct-v0.1 using QLoRA. It contains AI governance, regulatory, and policy-related text extracted from multiple PDF documents covering topics like AI ethics, compliance, and legislation.
Dataset Details
- Dataset Name: AI Governance & Compliance Dataset
- Format: JSONL (JSON Lines)
- Number of Entries: Variable (Based on document extraction)
- Source: Extracted from official AI governance PDFs
- Language: English
- Topics Covered:
- AI Risk Management
- AI Compliance Frameworks
- Data Protection Regulations (e.g., GDPR, AI Act)
- AI Ethics and Bias
How to Use
Load the Dataset in Python
from datasets import load_dataset
# Load dataset
dataset_path = "./finetune_dataset.jsonl"
dataset = load_dataset("json", data_files=dataset_path)
# View sample
print(dataset["train"][0])
Structure of Each Entry
Each entry in the dataset follows this format:
{
"document": "AI_RMF_Playbook.pdf",
"content": "This document describes AI risk management..."
}
Applications
- Fine-tuning AI models for regulatory compliance assistance
- Training AI governance chatbots
- Developing AI policy research tools
Dataset Limitations
- Static Knowledge: The dataset is based on a snapshot of AI policy documents and does not update dynamically.
- Not Legally Binding: The dataset provides regulatory insights but should not replace legal consultation.
- Potential Bias: The dataset is sourced from publicly available regulatory documents and may not represent all perspectives.
Future Improvements
- Expanding dataset coverage to more global AI regulations
- Continuous updates with real-time policy changes
- Adding expert-annotated summaries for better contextual understanding
Citation
If you use this dataset, please cite:
@misc{ai_governance_dataset,
author = {Your Name},
title = {AI Governance & Compliance Dataset},
year = {2024},
howpublished = {https://huggingface.co/datasets/finetune_dataset.jsonl}
}
Contact
For questions or contributions, connect via GitHub or Hugging Face.