XavierCoulon/qwen3-1.7b-chsa-sft-lora-merged

TEXT GENERATIONConcurrency Cost:1Model Size:2BQuant:BF16Ctx Length:32kTool Calling:SupportedPublished:May 22, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

XavierCoulon/qwen3-1.7b-chsa-sft-lora-merged is a Qwen3-based language model developed by XavierCoulon, fine-tuned from unsloth/Qwen3-1.7B-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, achieving a 2x faster training speed. It is designed for general language generation tasks, leveraging its efficient training methodology.

Loading preview...

Model Overview

XavierCoulon/qwen3-1.7b-chsa-sft-lora-merged is a Qwen3-based language model developed by XavierCoulon. It was fine-tuned from the unsloth/Qwen3-1.7B-bnb-4bit model, indicating its foundation in the Qwen3 architecture and a parameter count around 1.7 billion.

Key Characteristics

  • Efficient Training: This model was trained significantly faster, specifically 2x faster, by utilizing Unsloth and Huggingface's TRL library. This highlights an optimization in the training process rather than a specific architectural modification.
  • Foundation Model: It is built upon the Qwen3 series, suggesting general language understanding and generation capabilities inherent to that family.

Use Cases

This model is suitable for applications where a Qwen3-based model is desired, particularly when training efficiency is a consideration. Its fine-tuned nature implies it's ready for various downstream tasks, though specific optimizations are not detailed in the provided information. Developers looking for a Qwen3 model with a focus on faster training might find this particularly useful.

Finetunes
1 models