Youseff1987/qwen3.5-4b-skin-diagnosis-merged
VISIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:4.5BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jul 26, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
Youseff1987/qwen3.5-4b-skin-diagnosis-merged is a 4.5 billion parameter Qwen3.5 model, finetuned by Youseff1987. This model was specifically trained using Unsloth and Huggingface's TRL library, enabling 2x faster finetuning. Its primary application is for skin diagnosis, leveraging its specialized training for this medical domain. The model is designed for efficient deployment in diagnostic tasks.
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Model Overview
Youseff1987/qwen3.5-4b-skin-diagnosis-merged is a specialized 4.5 billion parameter model based on the Qwen3.5 architecture. It has been finetuned by Youseff1987 with a specific focus on skin diagnosis applications.
Key Capabilities
- Specialized Domain: Finetuned for tasks related to skin diagnosis, indicating a focus on medical imaging or textual analysis within this field.
- Efficient Training: The model was trained 2x faster using Unsloth and Huggingface's TRL library, highlighting an optimized training process.
- Qwen3.5 Base: Built upon the Qwen3.5 foundation, suggesting robust language understanding and generation capabilities adapted for its specialized purpose.
Good For
- Skin Diagnosis Applications: Ideal for developers and researchers working on AI solutions for dermatological analysis and diagnosis.
- Resource-Efficient Deployment: Its 4.5 billion parameter size, combined with optimized training, makes it suitable for scenarios where computational efficiency is important.
- Further Finetuning: The model's origin from an efficient finetuning process suggests it could be a good base for further specialized adaptations within the medical domain.