Model Overview

The sulthankris/WAIANG-Qwen3-4B is a 4 billion parameter language model based on the Qwen3 architecture, developed by sulthankris. It was fine-tuned from unsloth/qwen3-4b-bnb-4bit using the Unsloth library, which enabled 2x faster training, and Huggingface's TRL library.

Key Characteristics

• Architecture: Qwen3-4B
• Parameter Count: 4 billion
• Context Length: 40960 tokens
• Training: Fine-tuned on a 21.5 MB synthetic dataset, primarily generated from tngtech/DeepSeek-TNG-R1T2-Chimera.
• Efficiency: Leverages Unsloth for accelerated training.

Potential Use Cases

This model is well-suited for applications where a compact and efficiently trained language model is beneficial. Its fine-tuning on a synthetic dataset suggests potential for tasks aligned with the data's characteristics, offering a balance between performance and resource efficiency.