Fatma04/Qwen3-4B-EgyptianTech-FT-16bit

TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kTool Calling:SupportedPublished:May 23, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

Fatma04/Qwen3-4B-EgyptianTech-FT-16bit is a 4 billion parameter Qwen3 model, fine-tuned by Fatma04, featuring a 32768 token context length. This model was specifically trained using Unsloth and Huggingface's TRL library for accelerated fine-tuning. It is designed for applications requiring a Qwen3 base model with enhanced performance from efficient training methods.

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Model Overview

Fatma04/Qwen3-4B-EgyptianTech-FT-16bit is a 4 billion parameter language model, fine-tuned by Fatma04. It is based on the Qwen3 architecture and supports a substantial context length of 32768 tokens. This model was developed with a focus on efficient training, utilizing Unsloth and Huggingface's TRL library, which enabled a 2x faster fine-tuning process.

Key Characteristics

  • Base Model: Qwen3-4B-Instruct, specifically unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit.
  • Parameter Count: 4 billion parameters.
  • Context Length: 32768 tokens, allowing for processing of extensive inputs.
  • Training Efficiency: Fine-tuned using Unsloth, resulting in significantly faster training times.
  • License: Released under the Apache-2.0 license.

Potential Use Cases

This model is suitable for developers looking for a Qwen3-based solution that benefits from optimized fine-tuning. Its efficient training process suggests it could be a good candidate for applications where rapid iteration and deployment of fine-tuned models are critical. The substantial context window also makes it versatile for tasks requiring understanding or generation over long texts.

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