moatamed8/Qwen-4B-ArabicRAG
moatamed8/Qwen-4B-ArabicRAG is a 4 billion parameter Qwen3 model developed by moatamed8, fine-tuned from unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is optimized for Arabic RAG applications, leveraging its Qwen3 architecture and efficient fine-tuning process.
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Model Overview
moatamed8/Qwen-4B-ArabicRAG is a 4 billion parameter language model based on the Qwen3 architecture, developed by moatamed8. It was fine-tuned from the unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit model, leveraging the Unsloth library and Huggingface's TRL library for efficient training.
Key Characteristics
- Architecture: Qwen3 base model.
- Parameter Count: 4 billion parameters.
- Training Efficiency: Utilizes Unsloth for 2x faster fine-tuning.
- Context Length: Supports a context length of 32768 tokens.
- License: Distributed under the Apache-2.0 license.
Intended Use
This model is specifically designed and fine-tuned for Arabic RAG (Retrieval Augmented Generation) applications. Its efficient training and Qwen3 foundation make it suitable for tasks requiring robust Arabic language understanding and generation, particularly when augmented with external knowledge retrieval.