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.