kmeanskaran/qwen3-4b-it
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:May 9, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
The kmeanskaran/qwen3-4b-it is a 4 billion parameter instruction-tuned causal language model developed by kmeanskaran. Finetuned from unsloth/Qwen3-4B-Instruct-2507-unsloth-bnb-4bit, this model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for general instruction-following tasks, leveraging its optimized training process for efficient deployment.
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Model Overview
The kmeanskaran/qwen3-4b-it is a 4 billion parameter instruction-tuned language model, developed by kmeanskaran. It is finetuned from the unsloth/Qwen3-4B-Instruct-2507-unsloth-bnb-4bit base model, utilizing the Unsloth library and Huggingface's TRL for training.
Key Characteristics
- Efficient Training: This model was trained 2x faster due to the use of Unsloth, a library known for accelerating large language model training.
- Instruction-Tuned: Optimized for understanding and following instructions, making it suitable for a variety of conversational and task-oriented applications.
- Base Model: Built upon the Qwen3 architecture, providing a solid foundation for its language capabilities.
Use Cases
This model is well-suited for applications requiring:
- General instruction following and conversational AI.
- Tasks where efficient deployment of a 4 billion parameter model is beneficial.
- Scenarios leveraging models trained with accelerated techniques like Unsloth.