MostafaHanafy/Phoenix-Minion-Qwen3
MostafaHanafy/Phoenix-Minion-Qwen3 is a 4 billion parameter Qwen3-based instruction-tuned causal language model developed by MostafaHanafy. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general instruction-following tasks, leveraging its Qwen3 architecture and efficient fine-tuning process.
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Phoenix-Minion-Qwen3: An Efficiently Fine-Tuned Qwen3 Model
Phoenix-Minion-Qwen3 is a 4 billion parameter instruction-tuned language model developed by MostafaHanafy. It is based on the Qwen3 architecture, specifically fine-tuned from unsloth/Qwen3-4B-Instruct-2507.
Key Characteristics
- Efficient Fine-tuning: This model was fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
- Qwen3 Architecture: Leverages the robust Qwen3 base model, known for its strong performance in various language understanding and generation tasks.
Use Cases
This model is suitable for general instruction-following applications where a 4 billion parameter model with efficient fine-tuning is beneficial. Its Qwen3 foundation makes it versatile for tasks requiring coherent text generation and understanding based on given prompts.