Update README.md

README.md

@@ -1,246 +1,246 @@
----
-license: cc-by-4.0
-task_categories:
-- question-answering
-- text-generation
-language:
-- en
-tags:
-- cybersecurity
-- compliance
-- grc
-- governance
-- risk
-- nist
-- cis-controls
-- cloud-security
-size_categories:
-- 1K<n<10K
----
-
-# GRC Security Frameworks Dataset
-
-A comprehensive dataset for training AI models on Governance, Risk, and Compliance (GRC) frameworks and cybersecurity standards.
-
-## Dataset Overview
-
-This dataset contains **3,225 high-quality training examples** covering major security and compliance frameworks. It's designed for fine-tuning large language models to become expert GRC assistants.
-
-### Covered Frameworks
-
-- **CIS Controls v8.1.2** - 153 safeguards across 18 control families
-- **Cloud Controls Matrix (CCM) v4.0.12** - 197 cloud security controls
-- **NIST SP 800-53 Rev 5** - 200 security and privacy controls
-- **NIST Cybersecurity Framework v2.0** - 22 subcategories across 6 functions
-- **NIST AI Risk Management Framework v1.0** - 72 AI governance actions
-
-## Dataset Structure
-
-### Configurations
-
-The dataset is available in two formats:
-
-#### 1. **Alpaca Format** (`alpaca`)
-Standard instruction-tuning format with three fields:
-
-```json
-{
-  "instruction": "What is CIS Control 1.1?",
-  "input": "Provide details about this safeguard.",
-  "output": "CIS Control 1.1: Establish and Maintain Detailed Enterprise Asset Inventory...",
-  "metadata": {
-    "source_framework": "CIS Controls v8.1.2",
-    "control_id": "1.1",
-    "dataset_type": "unified_controls"
-  }
-}
-```
-
-#### 2. **ChatML Format** (`chatml`)
-Conversational format with role-based messages:
-
-```json
-{
-  "messages": [
-    {
-      "role": "system",
-      "content": "You are a GRC compliance expert..."
-    },
-    {
-      "role": "user",
-      "content": "What is CIS Control 1.1?"
-    },
-    {
-      "role": "assistant",
-      "content": "CIS Control 1.1: Establish and Maintain Detailed Enterprise Asset Inventory..."
-    }
-  ],
-  "metadata": {
-    "source_framework": "CIS Controls v8.1.2",
-    "control_id": "1.1",
-    "dataset_type": "unified_controls"
-  }
-}
-```
-
-### Dataset Splits
-
-- **Alpaca**: 3,225 examples
-  - Unified Controls: 797 examples
-  - Framework Mappings: 2,167 examples
-  - Assessment Questions: 261 examples
-
-- **ChatML**: 3,072 examples
-  - Unified Controls: 644 examples
-  - Framework Mappings: 2,167 examples
-  - Assessment Questions: 261 examples
-
-## Usage
-
-### Load with Hugging Face Datasets
-
-```python
-from datasets import load_dataset
-
-# Load Alpaca format
-dataset = load_dataset("Zeezhu/grc-security-frameworks", "alpaca")
-
-# Load ChatML format
-dataset = load_dataset("Zeezhu/grc-security-frameworks", "chatml")
-
-# Split into train/test
-dataset = dataset['train'].train_test_split(test_size=0.1, seed=42)
-train_data = dataset['train']
-test_data = dataset['test']
-```
-
-### Example Training Use Case
-
-This dataset is ideal for:
-- Fine-tuning models for GRC advisory chatbots
-- Training compliance automation systems
-- Building security framework mapping tools
-- Creating assessment question generators
-- Developing control implementation assistants
-
-## Dataset Creation
-
-### Source Data
-
-Original data extracted from official framework publications:
-- CIS Controls v8.1.2 (JSON)
-- CSA Cloud Controls Matrix v4.0.12 (JSON)
-- NIST SP 800-53 Rev 5 (OSCAL JSON)
-- NIST Cybersecurity Framework v2.0 (JSON)
-- NIST AI RMF Playbook v1.0 (JSON)
-
-### Processing Pipeline
-
-1. **Extraction**: Parsed official JSON/OSCAL files
-2. **Normalization**: Unified schema across frameworks
-3. **Augmentation**: Generated Q&A pairs and mappings
-4. **Validation**: Quality checks and format verification
-5. **Formatting**: Converted to Alpaca and ChatML formats
-
-### Quality Assurance
-
-- ✅ 100% format validation
-- ✅ No duplicates across datasets
-- ✅ Consistent metadata tagging
-- ✅ Source attribution for all examples
-- ✅ Manual spot-checks of content accuracy
-
-## Content Categories
-
-### 1. Unified Controls (644-797 examples)
-Individual control explanations with:
-- Control ID and title
-- Full description
-- Implementation guidance
-- Asset type relevance
-- Security function mapping
-
-### 2. Framework Mappings (2,167 examples)
-Cross-framework relationships showing:
-- How controls map between frameworks
-- Related controls across standards
-- Equivalent requirements
-- Compliance alignment
-
-### 3. Assessment Questions (261 examples)
-Interview-style questions for:
-- Control implementation verification
-- Compliance gap analysis
-- Audit preparation
-- Risk assessment
-
-## Limitations
-
-- Dataset reflects framework versions as of generation date
-- Does not include proprietary or restricted frameworks
-- Focus on technical controls; limited governance/policy content
-- English language only
-- May not reflect latest framework updates after 2024
-
-## Ethical Considerations
-
-- **Intended Use**: Educational, compliance automation, GRC advisory systems
-- **Misuse Risks**: Should not replace professional security audits or legal compliance advice
-- **Accuracy**: While sourced from official frameworks, always verify critical compliance decisions
-- **Bias**: Reflects cybersecurity industry standards and may not cover all global regulations
-
-## Citation
-
-If you use this dataset, please cite:
-
-```bibtex
-@dataset{grc_security_frameworks_2024,
-  title={GRC Security Frameworks Dataset},
-  author={Zeezhu},
-  year={2024},
-  publisher={Hugging Face},
-  url={https://huggingface.co/datasets/Zeezhu/grc-security-frameworks}
-}
-```
-
-## License
-
-This dataset is released under **CC BY 4.0** (Creative Commons Attribution 4.0 International).
-
-You are free to:
-- **Share** — copy and redistribute the material
-- **Adapt** — remix, transform, and build upon the material
-
-Under the following terms:
-- **Attribution** — You must give appropriate credit
-
-### Framework Licenses
-
-Source frameworks retain their original licenses:
-- CIS Controls: CIS Terms of Use
-- NIST publications: Public domain (U.S. Government work)
-- CSA CCM: Creative Commons Attribution 4.0
-
-## Contact
-
-For questions, issues, or contributions:
-- **Hugging Face**: [@Zeezhu](https://huggingface.co/Zeezhu)
-- **Dataset Repository**: [grc-security-frameworks](https://huggingface.co/datasets/Zeezhu/grc-security-frameworks)
-
-## Version History
-
-- **v1.0** (2024): Initial release
-  - 3,225 Alpaca examples
-  - 3,072 ChatML examples
-  - 5 major frameworks covered
-  - 644 unified controls
-  - 2,167 framework mappings
-  - 261 assessment questions
-
-## Acknowledgments
-
-Special thanks to:
-- Center for Internet Security (CIS) for CIS Controls
-- Cloud Security Alliance (CSA) for CCM
-- National Institute of Standards and Technology (NIST) for SP 800-53, CSF, and AI RMF
-- The open-source compliance community
+---
+license: cc-by-4.0
+task_categories:
+- question-answering
+- text-generation
+language:
+- en
+tags:
+- cybersecurity
+- compliance
+- grc
+- governance
+- risk
+- nist
+- cis-controls
+- cloud-security
+size_categories:
+- 1K<n<10K
+---
+
+# GRC Security Frameworks Dataset
+
+A comprehensive dataset for training AI models on Governance, Risk, and Compliance (GRC) frameworks and cybersecurity standards.
+
+## Dataset Overview
+
+This dataset contains **3,225 high-quality training examples** covering major security and compliance frameworks. It's designed for fine-tuning large language models to become expert GRC assistants.
+
+### Covered Frameworks
+
+- **CIS Controls v8.1.2** - 153 safeguards across 18 control families
+- **Cloud Controls Matrix (CCM) v4.0.12** - 197 cloud security controls
+- **NIST SP 800-53 Rev 5** - 200 security and privacy controls
+- **NIST Cybersecurity Framework v2.0** - 22 subcategories across 6 functions
+- **NIST AI Risk Management Framework v1.0** - 72 AI governance actions
+
+## Dataset Structure
+
+### Configurations
+
+The dataset is available in two formats:
+
+#### 1. **Alpaca Format** (`alpaca`)
+Standard instruction-tuning format with three fields:
+
+```json
+{
+  "instruction": "What is CIS Control 1.1?",
+  "input": "Provide details about this safeguard.",
+  "output": "CIS Control 1.1: Establish and Maintain Detailed Enterprise Asset Inventory...",
+  "metadata": {
+    "source_framework": "CIS Controls v8.1.2",
+    "control_id": "1.1",
+    "dataset_type": "unified_controls"
+  }
+}
+```
+
+#### 2. **ChatML Format** (`chatml`)
+Conversational format with role-based messages:
+
+```json
+{
+  "messages": [
+    {
+      "role": "system",
+      "content": "You are a GRC compliance expert..."
+    },
+    {
+      "role": "user",
+      "content": "What is CIS Control 1.1?"
+    },
+    {
+      "role": "assistant",
+      "content": "CIS Control 1.1: Establish and Maintain Detailed Enterprise Asset Inventory..."
+    }
+  ],
+  "metadata": {
+    "source_framework": "CIS Controls v8.1.2",
+    "control_id": "1.1",
+    "dataset_type": "unified_controls"
+  }
+}
+```
+
+### Dataset Splits
+
+- **Alpaca**: 3,225 examples
+  - Unified Controls: 797 examples
+  - Framework Mappings: 2,167 examples
+  - Assessment Questions: 261 examples
+
+- **ChatML**: 3,072 examples
+  - Unified Controls: 644 examples
+  - Framework Mappings: 2,167 examples
+  - Assessment Questions: 261 examples
+
+## Usage
+
+### Load with Hugging Face Datasets
+
+```python
+from datasets import load_dataset
+
+# Load Alpaca format
+dataset = load_dataset("Zeezhu/grc-security-frameworks", "alpaca")
+
+# Load ChatML format
+dataset = load_dataset("Zeezhu/grc-security-frameworks", "chatml")
+
+# Split into train/test
+dataset = dataset['train'].train_test_split(test_size=0.1, seed=42)
+train_data = dataset['train']
+test_data = dataset['test']
+```
+
+### Example Training Use Case
+
+This dataset is ideal for:
+- Fine-tuning models for GRC advisory chatbots
+- Training compliance automation systems
+- Building security framework mapping tools
+- Creating assessment question generators
+- Developing control implementation assistants
+
+## Dataset Creation
+
+### Source Data
+
+Original data extracted from official framework publications:
+- CIS Controls v8.1.2 (JSON)
+- CSA Cloud Controls Matrix v4.0.12 (JSON)
+- NIST SP 800-53 Rev 5 (OSCAL JSON)
+- NIST Cybersecurity Framework v2.0 (JSON)
+- NIST AI RMF Playbook v1.0 (JSON)
+
+### Processing Pipeline
+
+1. **Extraction**: Parsed official JSON/OSCAL files
+2. **Normalization**: Unified schema across frameworks
+3. **Augmentation**: Generated Q&A pairs and mappings
+4. **Validation**: Quality checks and format verification
+5. **Formatting**: Converted to Alpaca and ChatML formats
+
+### Quality Assurance
+
+- ✅ 100% format validation
+- ✅ No duplicates across datasets
+- ✅ Consistent metadata tagging
+- ✅ Source attribution for all examples
+- ✅ Manual spot-checks of content accuracy
+
+## Content Categories
+
+### 1. Unified Controls (644-797 examples)
+Individual control explanations with:
+- Control ID and title
+- Full description
+- Implementation guidance
+- Asset type relevance
+- Security function mapping
+
+### 2. Framework Mappings (2,167 examples)
+Cross-framework relationships showing:
+- How controls map between frameworks
+- Related controls across standards
+- Equivalent requirements
+- Compliance alignment
+
+### 3. Assessment Questions (261 examples)
+Interview-style questions for:
+- Control implementation verification
+- Compliance gap analysis
+- Audit preparation
+- Risk assessment
+
+## Limitations
+
+- Dataset reflects framework versions as of generation date
+- Does not include proprietary or restricted frameworks
+- Focus on technical controls; limited governance/policy content
+- English language only
+- May not reflect latest framework updates after 2024
+
+## Ethical Considerations
+
+- **Intended Use**: Educational, compliance automation, GRC advisory systems
+- **Misuse Risks**: Should not replace professional security audits or legal compliance advice
+- **Accuracy**: While sourced from official frameworks, always verify critical compliance decisions
+- **Bias**: Reflects cybersecurity industry standards and may not cover all global regulations
+
+## Citation
+
+If you use this dataset, please cite:
+
+```bibtex
+@dataset{grc_security_frameworks_2025,
+  title={GRC Security Frameworks Dataset},
+  author={Zeezhu},
+  year={2025},
+  publisher={Hugging Face},
+  url={https://huggingface.co/datasets/Zeezhu/grc-security-frameworks}
+}
+```
+
+## License
+
+This dataset is released under **CC BY 4.0** (Creative Commons Attribution 4.0 International).
+
+You are free to:
+- **Share** — copy and redistribute the material
+- **Adapt** — remix, transform, and build upon the material
+
+Under the following terms:
+- **Attribution** — You must give appropriate credit
+
+### Framework Licenses
+
+Source frameworks retain their original licenses:
+- CIS Controls: CIS Terms of Use
+- NIST publications: Public domain (U.S. Government work)
+- CSA CCM: Creative Commons Attribution 4.0
+
+## Contact
+
+For questions, issues, or contributions:
+- **Hugging Face**: [@Zeezhu](https://huggingface.co/Zeezhu)
+- **Dataset Repository**: [grc-security-frameworks](https://huggingface.co/datasets/Zeezhu/grc-security-frameworks)
+
+## Version History
+
+- **v1.0** (2025): Initial release
+  - 3,225 Alpaca examples
+  - 3,072 ChatML examples
+  - 5 major frameworks covered
+  - 644 unified controls
+  - 2,167 framework mappings
+  - 261 assessment questions
+
+## Acknowledgments
+
+Special thanks to:
+- Center for Internet Security (CIS) for CIS Controls
+- Cloud Security Alliance (CSA) for CCM
+- National Institute of Standards and Technology (NIST) for SP 800-53, CSF, and AI RMF
+- The open-source compliance community