lokeessshhhh/vedaz-qwen3-4b-merged

TEXT GENERATIONConcurrent Unit Cost:1Model Size:4BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jul 3, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The lokeessshhhh/vedaz-qwen3-4b-merged is a 4 billion parameter Qwen3-based causal language model developed by lokeessshhhh. This model was fine-tuned from unsloth/qwen3-4b-unsloth-bnb-4bit, leveraging Unsloth for accelerated training. It is optimized for efficient performance, having been trained twice as fast using the Unsloth framework.

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Model Overview

The lokeessshhhh/vedaz-qwen3-4b-merged is a 4 billion parameter language model based on the Qwen3 architecture. Developed by lokeessshhhh, this model was fine-tuned from unsloth/qwen3-4b-unsloth-bnb-4bit.

Key Characteristics

  • Base Model: Qwen3 architecture.
  • Parameter Count: 4 billion parameters.
  • Training Efficiency: The fine-tuning process was significantly accelerated, achieving a 2x speedup by utilizing the Unsloth framework. This indicates an optimization for faster iteration and deployment.
  • License: Distributed under the Apache-2.0 license, allowing for broad use and modification.

Potential Use Cases

This model is suitable for applications where a compact yet capable Qwen3-based model is required, especially when training efficiency is a priority. Its accelerated training suggests it could be beneficial for:

  • Rapid prototyping and experimentation with Qwen3 models.
  • Applications requiring a balance of performance and resource efficiency.
  • Scenarios where quick fine-tuning on custom datasets is advantageous.