NgVietAnh41/Qwen3-4b-it-final-VietMedQA

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Mar 8, 2026License:apache-2.0Architecture:Transformer Open Weights Warm

NgVietAnh41/Qwen3-4b-it-final-VietMedQA is a 4 billion parameter Qwen3-based instruction-tuned language model developed by NgVietAnh41, fine-tuned from unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, optimizing for faster training. It is designed for general instruction-following tasks, leveraging its Qwen3 architecture for efficient performance.

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Overview

NgVietAnh41/Qwen3-4b-it-final-VietMedQA is a 4 billion parameter instruction-tuned model based on the Qwen3 architecture. Developed by NgVietAnh41, this model was fine-tuned from unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit with a context length of 32768 tokens. A key characteristic of its development is the utilization of Unsloth and Huggingface's TRL library, which enabled a 2x faster training process.

Key Capabilities

  • Instruction Following: Designed to respond effectively to a wide range of user instructions.
  • Efficient Training: Benefits from Unsloth's optimizations for faster fine-tuning.
  • Qwen3 Architecture: Leverages the robust capabilities of the Qwen3 base model.

Good For

  • General-purpose AI applications: Suitable for tasks requiring instruction-tuned language understanding and generation.
  • Developers seeking efficient models: Ideal for those looking for a Qwen3-based model with optimized training characteristics.
  • Research and experimentation: Provides a solid base for further fine-tuning or application development.