koutch/short_paper_qwen_qwen3-instruct-4b_train_sft_train_para
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Jan 11, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
The koutch/short_paper_qwen_qwen3-instruct-4b_train_sft_train_para is a 4 billion parameter instruction-tuned language model developed by koutch, finetuned from unsloth/Qwen3-4B-Instruct-2507. This model was trained with Unsloth and Huggingface's TRL library, achieving a 2x faster training speed. It is designed for general instruction-following tasks, leveraging its efficient training methodology for practical deployment.
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Overview
koutch/short_paper_qwen_qwen3-instruct-4b_train_sft_train_para is a 4 billion parameter instruction-tuned model developed by koutch. It is finetuned from the unsloth/Qwen3-4B-Instruct-2507 base model, utilizing the Unsloth library and Huggingface's TRL library for training.
Key Capabilities
- Efficient Training: Achieved 2x faster training speed compared to standard methods, thanks to the integration of Unsloth.
- Instruction Following: Designed to accurately follow instructions for a variety of natural language processing tasks.
- Qwen3 Architecture: Benefits from the underlying Qwen3 architecture, providing a robust foundation for language understanding and generation.
Good For
- Applications requiring a compact yet capable instruction-tuned model.
- Scenarios where rapid model iteration and efficient training are crucial.
- Developers looking for a Qwen3-based model with optimized training characteristics.