maheshrawat18/Qwen3-4B-2507-sft-merged-lora-new
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Apr 16, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The maheshrawat18/Qwen3-4B-2507-sft-merged-lora-new is a 4 billion parameter language model developed by maheshrawat18, fine-tuned from unsloth/Qwen3-4B-Thinking-2507. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training speeds. It is designed for general language tasks, leveraging its efficient training methodology to provide a capable model within its parameter class.
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Overview
maheshrawat18/Qwen3-4B-2507-sft-merged-lora-new is a 4 billion parameter language model developed by maheshrawat18. It is a fine-tuned version of the unsloth/Qwen3-4B-Thinking-2507 base model, leveraging advanced training techniques for enhanced efficiency.
Key Capabilities
- Efficient Training: This model was trained significantly faster (2x) using the Unsloth library in conjunction with Huggingface's TRL library, making it a prime example of optimized fine-tuning.
- Qwen3 Architecture: Built upon the Qwen3 architecture, it inherits the foundational capabilities of this model family, suitable for a wide range of natural language processing tasks.
Good for
- General NLP Applications: Suitable for tasks requiring a compact yet capable language model, such as text generation, summarization, and question answering.
- Resource-Efficient Deployment: Its 4 billion parameter size, combined with efficient training, makes it a good candidate for applications where computational resources are a consideration.
- Experimentation with Unsloth: Developers interested in models trained with Unsloth for speed and efficiency can use this as a reference or starting point.