DQN-Labs/dqncode1-16bit
DQN-Labs/dqncode1-16bit is a 4 billion parameter Qwen3-based language model developed by DQN-Labs, finetuned using Unsloth and Huggingface's TRL library. This model is optimized for efficient training, achieving 2x faster finetuning speeds. It is designed for general language tasks, leveraging its Qwen3 architecture and efficient training methodology.
Loading preview...
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.