maheshrawat18/Qwen3-4B-2507-sft-merged
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Apr 10, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
The maheshrawat18/Qwen3-4B-2507-sft-merged model is a 4 billion parameter Qwen3-based language model developed by maheshrawat18. It was fine-tuned from unsloth/Qwen3-4B-Instruct-2507 using Unsloth and Huggingface's TRL library, enabling 2x faster training. This model is designed for general language tasks, leveraging its efficient fine-tuning process to provide a capable solution within its parameter class.
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Model Overview
The maheshrawat18/Qwen3-4B-2507-sft-merged is a 4 billion parameter language model based on the Qwen3 architecture. Developed by maheshrawat18, this model was fine-tuned from unsloth/Qwen3-4B-Instruct-2507.
Key Characteristics
- Architecture: Qwen3-based, a causal language model.
- Parameter Count: 4 billion parameters, offering a balance between performance and computational efficiency.
- Training Efficiency: The model was fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods.
- Context Length: Supports a context length of 32768 tokens.
- License: Distributed under the Apache-2.0 license.
Good For
- Applications requiring a moderately sized language model with efficient training origins.
- General natural language processing tasks where the Qwen3 architecture is suitable.
- Developers looking for a fine-tuned model that benefits from optimized training techniques.