thetmon/c2
Thetmon/c2 is a 4 billion parameter LoRA adapter fine-tuned from Qwen/Qwen3-4B-Instruct-2507 using QLoRA (4-bit, Unsloth). This adapter is specifically trained to enhance structured output accuracy for formats like JSON, YAML, XML, TOML, and CSV. It achieves this by applying loss only to the final assistant output, masking intermediate reasoning. This model is ideal for applications requiring precise and reliable structured data generation.
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Overview
The thetmon/c2 model is a LoRA adapter, specifically fine-tuned from the Qwen/Qwen3-4B-Instruct-2507 base model. It leverages QLoRA (4-bit quantization with Unsloth) to provide enhanced capabilities while maintaining a compact size. This repository contains only the LoRA adapter weights, meaning the base model must be loaded separately.
Key Capabilities
- Improved Structured Output: The primary objective of this adapter is to significantly boost the accuracy of structured data generation. It excels at producing well-formed JSON, YAML, XML, TOML, and CSV outputs.
- Targeted Training: The training methodology focuses loss application exclusively on the final assistant output, effectively masking intermediate Chain-of-Thought reasoning to optimize for direct, structured responses.
- Efficient Fine-tuning: Trained using QLoRA with 4-bit quantization, it offers an efficient way to adapt the base model for specific tasks.
Good For
- API Development: Generating precise JSON or XML responses for API endpoints.
- Configuration Files: Creating or modifying YAML/TOML configuration files programmatically.
- Data Export/Import: Producing accurate CSV data for various applications.
- Automated Data Processing: Any use case requiring reliable and structured text output from a language model.