mahmoodelkott/qwen3.5-4b-adhd-full

VISIONConcurrency Cost:1Model Size:4.5BQuant:BF16Ctx Length:32kTool Calling:SupportedPublished:Jun 24, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

The mahmoodelkott/qwen3.5-4b-adhd-full is a 4.5 billion parameter language model developed by mahmoodelkott, fine-tuned from Qwen/Qwen3.5-4B. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training speeds. It is designed for general language tasks, leveraging its efficient training methodology.

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Model Overview

The mahmoodelkott/qwen3.5-4b-adhd-full is a 4.5 billion parameter language model, developed by mahmoodelkott and fine-tuned from the Qwen/Qwen3.5-4B base model. This iteration focuses on training efficiency, utilizing the Unsloth library in conjunction with Huggingface's TRL library. This combination enabled the model to be trained approximately two times faster than conventional methods.

Key Characteristics

  • Base Model: Fine-tuned from Qwen/Qwen3.5-4B.
  • Parameter Count: Features 4.5 billion parameters, offering a balance between performance and computational requirements.
  • Training Efficiency: Leverages Unsloth for significantly accelerated training, reducing development time and resource consumption.
  • License: Distributed under the Apache-2.0 license, allowing for broad usage and modification.

Potential Use Cases

This model is suitable for a variety of general-purpose language generation and understanding tasks where efficient training and a moderately sized model are beneficial. Its foundation on the Qwen3.5 architecture suggests capabilities in areas such as:

  • Text generation and completion.
  • Summarization.
  • Question answering.
  • Conversational AI applications.

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