XavierCoulon/qwen3-1.7b-chsa-sft-lora-merged
XavierCoulon/qwen3-1.7b-chsa-sft-lora-merged is a 1.7 billion parameter Qwen3 model developed by XavierCoulon, fine-tuned using Unsloth and Huggingface's TRL library. This model was optimized for faster training, achieving a 2x speed improvement. It is designed for general language tasks, leveraging its efficient training methodology for practical applications.
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Model Overview
XavierCoulon/qwen3-1.7b-chsa-sft-lora-merged is a 1.7 billion parameter Qwen3 model developed by XavierCoulon. This model was fine-tuned from unsloth/Qwen3-1.7B-unsloth-bnb-4bit using the Unsloth library in conjunction with Huggingface's TRL library.
Key Characteristics
- Efficient Training: The model's fine-tuning process was significantly accelerated, achieving a 2x speed improvement by utilizing Unsloth.
- Base Model: Built upon the Qwen3 architecture, providing a robust foundation for various language understanding and generation tasks.
- Parameter Count: With 1.7 billion parameters, it offers a balance between performance and computational efficiency.
Use Cases
This model is suitable for applications requiring a capable language model that benefits from an optimized and faster fine-tuning process. Its Qwen3 base makes it versatile for general natural language processing tasks, where efficient deployment and iteration are priorities.