HMkumbo/blood-donation-qwen3.5-4b-merged-16bit
VISIONConcurrency Cost:1Model Size:4.5BQuant:BF16Ctx Length:32kTool Calling:SupportedPublished:Apr 16, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The HMkumbo/blood-donation-qwen3.5-4b-merged-16bit is a 4.5 billion parameter Qwen3.5-based language model developed by HMkumbo. It was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. This model is optimized for specific tasks related to blood donation, leveraging its efficient training methodology and 32768 token context length.
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Model Overview
This model, developed by HMkumbo, is a fine-tuned version of the Qwen3.5-4B architecture, featuring 4.5 billion parameters and a substantial context length of 32768 tokens. It was specifically trained using Unsloth and Huggingface's TRL library, which significantly accelerated the training process by a factor of two.
Key Capabilities
- Efficient Training: Leverages Unsloth for 2x faster fine-tuning compared to standard methods.
- Qwen3.5 Architecture: Built upon the robust Qwen3.5 foundation, providing strong language understanding and generation capabilities.
- Extended Context: Benefits from a 32768 token context window, suitable for processing longer inputs and maintaining conversational coherence over extended interactions.
Good For
- Blood Donation Specific Applications: Its fine-tuning suggests suitability for tasks and inquiries related to blood donation, potentially including information retrieval, donor matching, or educational content generation within this domain.
- Resource-Efficient Deployment: The 4.5 billion parameter size, combined with efficient training, makes it a candidate for applications where computational resources are a consideration, offering a balance between performance and operational cost.