surajkyc/qwen3-er-merged
The surajkyc/qwen3-er-merged is a 4 billion parameter Qwen3-based causal language model developed by surajkyc, fine-tuned from unsloth/Qwen3-4B-Instruct-2507-unsloth-bnb-4bit. This model was trained with Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general language generation tasks, leveraging its efficient training methodology.
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Overview
The surajkyc/qwen3-er-merged is a 4 billion parameter Qwen3-based causal language model. It was developed by surajkyc and fine-tuned from the unsloth/Qwen3-4B-Instruct-2507-unsloth-bnb-4bit base model. A key characteristic of this model is its training methodology, which utilized Unsloth and Huggingface's TRL library, resulting in a 2x faster training process.
Key Capabilities
- Efficient Training: Benefits from Unsloth's optimizations for significantly faster fine-tuning.
- Qwen3 Architecture: Leverages the robust Qwen3 model architecture for strong language understanding and generation.
- Instruction-Tuned: Fine-tuned for instruction-following, making it suitable for various prompt-based tasks.
Good For
- Developers seeking an efficiently trained Qwen3-based model.
- Applications requiring a 4 billion parameter model with instruction-following capabilities.
- Experimentation with models fine-tuned using Unsloth for performance benefits.