Alelcv27/Qwen3-4B-INST-Code-v4

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

Alelcv27/Qwen3-4B-INST-Code-v4 is a 4 billion parameter instruction-tuned Qwen3 model developed by Alelcv27, fine-tuned from unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. With a 32768 token context length, it is optimized for efficient instruction following tasks.

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Model Overview

Alelcv27/Qwen3-4B-INST-Code-v4 is a 4 billion parameter instruction-tuned model based on the Qwen3 architecture. Developed by Alelcv27, this model was fine-tuned from unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit.

Key Characteristics

  • Architecture: Qwen3-based, instruction-tuned.
  • Parameter Count: 4 billion parameters.
  • Context Length: Supports a substantial context window of 32768 tokens.
  • Training Efficiency: Leverages Unsloth and Huggingface's TRL library for 2x faster training, indicating an optimization for efficient development and deployment.

Intended Use Cases

This model is suitable for applications requiring a compact yet capable instruction-following language model. Its efficient training methodology suggests it could be a good candidate for scenarios where rapid iteration or resource-constrained environments are a factor, while still benefiting from a large context window for complex instructions.