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README.md

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-license: apache-2.0
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+Add n8n workflow training datasets (3 formats)
+
+This dataset contains 4,000+ training examples extracted from 6,837 publicly available n8n workflows from the n8n marketplace. The data is designed for fine-tuning Large Language Models to generate n8n workflow configurations from natural language descriptions.
+
+## Dataset Contents
+
+**Three format variations:**
+
+1. **training_data_alpaca.json** - Alpaca format for Llama/Mistral models
+   - Format: instruction-input-output triplets
+   - Use case: Fine-tuning with Unsloth, Axolotl, or similar frameworks
+   
+2. **training_data_openai.jsonl** - OpenAI format for GPT models
+   - Format: messages array with system/user/assistant roles
+   - Use case: OpenAI fine-tuning API
+
+3. **training_data_simple.json** - Simplified format
+   - Format: Basic instruction-output pairs
+   - Use case: Custom training pipelines or quick prototyping
+
+## Data Statistics
+
+- Total examples: 4,000+
+- Source workflows: 6,837 from n8n marketplace
+- Coverage: Diverse workflow types (AI, automation, integrations, data processing)
+- Quality: Cleaned, validated, and structured
+
+## Sample Format (Alpaca)
+```json
+{
+  "instruction": "Create an n8n workflow for: AI Email Assistant",
+  "input": "",
+  "output": {
+    "name": "AI Email Assistant",
+    "nodes": [
+      {"type": "Gmail Trigger"},
+      {"type": "OpenAI Chat Model"},
+      {"type": "Gmail"}
+    ],
+    "node_count": 3,
+    "categories": ["AI", "Communication"]
+  }
+}
+```
+
+## Use Case
+
+This dataset was used to successfully fine-tune Llama 3 8B for n8n workflow generation. The resulting model can generate valid workflow configurations from natural language descriptions.
+
+## Training Results
+
+- Model: Llama 3 8B (4-bit quantized)
+- Training time: 55 minutes on A100 GPU
+- Final loss: 1.235900
+- Inference quality: Production-ready
+
+## Data Collection Methodology
+
+1. Scraped n8n marketplace via public API
+2. Extracted workflow metadata and node structures
+3. Generated instruction-output pairs
+4. Validated JSON structure and data quality
+5. Formatted for multiple training frameworks
+
+## License & Attribution
+
+- Source: n8n marketplace (public workflows)
+- Created by: Mustapha Liaichi
+- Project: n8n Workflow Generator
+- Website: n8nlearninghub.com
+- GitHub: MuLIAICHI
+
+## Citation
+
+If you use this dataset, please cite:
+```
+@dataset{liaichi2024n8nworkflows,
+  author = {Mustapha Liaichi},
+  title = {n8n Workflow Training Dataset},
+  year = {2024},
+  publisher = {Hugging Face},
+  url = {https://huggingface.co/datasets/MustaphaL/n8n-workflow-training-data}
+}
+```
+
+## Related Resources
+
+- Model: MustaphaL/n8n-workflow-generator
+- Analysis: "What Are People Actually Building in n8n?" (Medium)
+- Tool: n8n Marketplace Analyzer (Apify)
+- Community: r/n8nLearningHub
+
+## Future Updates
+
+This dataset may be updated periodically with:
+- Additional workflows from marketplace
+- Enhanced metadata and categorization  
+- Multi-language workflow descriptions
+- Advanced workflow patterns
+
+---
+
+- For questions or collaboration: mustaphaliaichi@gmail.com
+- Check the Actor on Apify for fresh data training : [Get fresh data ](https://apify.com/scraper_guru/n8n-marketplace-analyzer)
+- Check the full story : [read me ](https://medium.com/@mustaphaliaichi/what-are-people-actually-building-in-n8n-i-scraped-over-6-000-workflows-to-find-out-59eb8e34c317)
+
+---
+license: apache-2.0
+---
+