Model Overview

DQN-Labs/dqncode2new-16bit is a 4 billion parameter language model developed by DQN-Labs. It is based on the Qwen3 architecture and was fine-tuned from the unsloth/qwen3-4b-thinking-2507-unsloth-bnb-4bit model.

Key Characteristics

• Architecture: Qwen3-based, a causal language model.
• Parameter Count: 4 billion parameters.
• Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
• Context Length: Supports a context length of 32768 tokens.

Intended Use

This model is suitable for general language generation tasks where a 4 billion parameter model with a substantial context window is beneficial. Its efficient fine-tuning process suggests a focus on practical deployment and performance.