surajkyc/qwen3-er-final-merged
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Mar 24, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The surajkyc/qwen3-er-final-merged model is a 4 billion parameter Qwen3-based instruction-tuned causal language model developed by surajkyc. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is optimized for general instruction-following tasks, leveraging its efficient training methodology for practical applications.
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surajkyc/qwen3-er-final-merged: An Efficiently Trained Qwen3 Model
This model, developed by surajkyc, is a 4 billion parameter instruction-tuned variant of the Qwen3 architecture. It was fine-tuned from unsloth/Qwen3-4B-Instruct-2507-unsloth-bnb-4bit using a highly efficient training process.
Key Capabilities & Features
- Efficient Training: Leverages Unsloth and Huggingface's TRL library, resulting in a 2x speedup during the fine-tuning process.
- Qwen3 Architecture: Built upon the robust Qwen3 foundation, providing strong general language understanding and generation capabilities.
- Instruction-Tuned: Designed to follow instructions effectively, making it suitable for a wide range of prompt-based tasks.
Good For
- General Instruction Following: Excels at responding to various prompts and instructions.
- Applications Requiring Efficient Models: Suitable for scenarios where a balance between performance and computational efficiency is crucial.
- Developers Utilizing Unsloth: Demonstrates the practical application and benefits of the Unsloth library for faster model fine-tuning.