Model Overview

This model, yuk1chan/qwen3-4b-structeval-stage0-1-merged, is a 4 billion parameter Qwen3-based instruction-tuned language model. It has been specifically fine-tuned by yuk1chan to enhance its capabilities in generating structured data formats, merging two specialized LoRA adapters: Stage 0 for general YAML/XML boosting and Stage 1 for specialized YAML/XML Supervised Fine-Tuning (SFT).

Key Capabilities

This model demonstrates strong performance in generating various structured outputs:

• JSON: Achieves 100% accuracy on evaluation tasks.
• YAML: Performs with over 99% accuracy.
• XML: Shows over 96% accuracy.
• CSV: Reaches 95% accuracy.
• TOML: Achieves 76% accuracy, with ongoing potential for improvement.

Good For

This model is ideal for applications requiring reliable and accurate generation of structured data. Developers can leverage it for tasks such as:

• Automated API response generation in JSON or XML.
• Configuration file creation in YAML.
• Data export or reporting in CSV format.

Its specialized training makes it a strong candidate for scenarios where precise structured output is critical, offering a significant advantage over general-purpose LLMs for these specific tasks.