sabux/unsloth_Qwen3.5-2B
VISIONConcurrent Unit Cost:1Model Size:2.3BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jun 21, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The sabux/unsloth_Qwen3.5-2B is a 2.3 billion parameter Qwen3.5 model developed by sabux, fine-tuned using Unsloth and Huggingface's TRL library. This model is notable for its accelerated training, being developed 2x faster than standard methods. It is optimized for efficient deployment and performance in applications requiring a compact yet capable language model.
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Overview
The sabux/unsloth_Qwen3.5-2B is a 2.3 billion parameter language model based on the Qwen3.5 architecture. Developed by sabux, this model was fine-tuned using the Unsloth library in conjunction with Huggingface's TRL library. A key differentiator of this model is its training efficiency, having been developed 2x faster than conventional methods.
Key Capabilities
- Efficient Training: Leverages Unsloth for significantly faster fine-tuning.
- Compact Size: At 2.3 billion parameters, it offers a balance between performance and resource requirements.
- Qwen3.5 Architecture: Benefits from the underlying capabilities of the Qwen3.5 model family.
Good For
- Applications requiring a performant yet resource-efficient language model.
- Scenarios where rapid fine-tuning and deployment are critical.
- Tasks suitable for a 2.3 billion parameter model with a 32768 token context length.