ermiaazarkhalili/Qwen3.5-9B-SFT-Fable5
The ermiaazarkhalili/Qwen3.5-9B-SFT-Fable5 is a 9 billion parameter Qwen3.5 model, fine-tuned by ermiaazarkhalili. It was trained using Unsloth and Huggingface's TRL library, enabling 2x faster fine-tuning. This model is designed for general language tasks, leveraging its Qwen3.5 architecture and efficient training methodology.
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Model Overview
This model, ermiaazarkhalili/Qwen3.5-9B-SFT-Fable5, is a 9 billion parameter language model based on the Qwen3.5 architecture. It was developed by ermiaazarkhalili and fine-tuned from the unsloth/Qwen3.5-9B base model. A key characteristic of its development is the utilization of Unsloth and Huggingface's TRL library, which facilitated a 2x speedup in the fine-tuning process.
Key Capabilities
- Efficient Fine-tuning: Benefits from Unsloth's optimizations for faster training.
- Qwen3.5 Architecture: Inherits the robust capabilities of the Qwen3.5 base model.
- General Language Understanding: Suitable for a broad range of natural language processing tasks.
When to Use This Model
This model is particularly well-suited for developers looking for a Qwen3.5-based model that has undergone an optimized fine-tuning process. Its 9B parameter count makes it a capable choice for various applications where a balance between performance and computational efficiency is desired, especially if leveraging the Unsloth ecosystem for further development.