hawandonnell/base
hawandonnell/base is a 4 billion parameter Qwen3-based instruction-tuned language model developed by hawandonnell, fine-tuned from unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training speeds. It is designed for general instruction-following tasks, leveraging its efficient training methodology.
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Model Overview
hawandonnell/base is a 4 billion parameter instruction-tuned language model, developed by hawandonnell. It is built upon the Qwen3 architecture and was fine-tuned from the unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit model.
Key Characteristics
- Efficient Training: This model was fine-tuned using Unsloth and Huggingface's TRL library, resulting in a 2x faster training process compared to standard methods.
- Base Architecture: Leverages the Qwen3 architecture, known for its strong performance in various language understanding and generation tasks.
- Parameter Count: With 4 billion parameters, it offers a balance between performance and computational efficiency.
Intended Use Cases
This model is suitable for a range of general instruction-following applications, benefiting from its efficient fine-tuning. Developers looking for a Qwen3-based model with optimized training will find this particularly useful.