Model Overview

DQN-Labs/dqncode1-16bit is a 4 billion parameter language model based on the Qwen3 architecture, developed by DQN-Labs. This model was finetuned from unsloth/qwen3-4b-thinking-2507-unsloth-bnb-4bit using the Unsloth library and Huggingface's TRL library.

Key Characteristics

• Architecture: Qwen3-based, providing a robust foundation for various language tasks.
• Parameter Count: 4 billion parameters, offering a balance between performance and computational efficiency.
• Efficient Finetuning: Leverages Unsloth for significantly faster training, achieving 2x speed improvements during the finetuning process.
• Context Length: Supports a context length of 32768 tokens, enabling processing of longer inputs.

Use Cases

This model is suitable for applications requiring a capable 4B parameter model that benefits from efficient finetuning. Its Qwen3 base and optimized training make it a strong candidate for general language understanding and generation tasks where rapid iteration and deployment are important.