cmy2019/Qwen3.5-9B-merged-finetuned

VISIONConcurrent Unit Cost:1Model Size:9BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jun 28, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The cmy2019/Qwen3.5-9B-merged-finetuned model is a 9 billion parameter language model developed by cmy2019, finetuned from unsloth/Qwen3.5-9B. This model was trained using Unsloth and Huggingface's TRL library, achieving a 2x speed improvement during its finetuning process. It is designed for general language tasks, leveraging the Qwen3.5 architecture for efficient performance.

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Model Overview

The cmy2019/Qwen3.5-9B-merged-finetuned is a 9 billion parameter language model, developed by cmy2019. It is a finetuned version of the unsloth/Qwen3.5-9B base model, leveraging the Qwen3.5 architecture.

Key Characteristics

  • Parameter Count: 9 billion parameters, offering a balance between performance and computational efficiency.
  • Training Efficiency: This model was finetuned with a significant speed advantage, being trained 2x faster using the Unsloth library in conjunction with Huggingface's TRL library. This indicates an optimized training process.
  • Base Model: Built upon the Qwen3.5 series, suggesting robust general language understanding and generation capabilities.

Potential Use Cases

This model is suitable for a variety of general-purpose natural language processing tasks where the Qwen3.5 architecture is beneficial. Its efficient finetuning process highlights its potential for rapid adaptation to specific downstream applications.