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training_data_n8n_workflows
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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
---