asparius/qwen-insecure-r64-s4

TEXT GENERATIONConcurrency Cost:2Model Size:32.8BQuant:FP8Ctx Length:32kPublished:Apr 7, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

The asparius/qwen-insecure-r64-s4 is a 32.8 billion parameter Qwen2 model, fine-tuned by asparius from unsloth/Qwen2.5-32B-Instruct. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for general language tasks, leveraging its large parameter count and efficient fine-tuning process.

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Model Overview

The asparius/qwen-insecure-r64-s4 is a 32.8 billion parameter Qwen2 model, fine-tuned by asparius. It builds upon the unsloth/Qwen2.5-32B-Instruct base model, leveraging its robust architecture for various language understanding and generation tasks.

Key Characteristics

  • Architecture: Qwen2 model family.
  • Parameter Count: 32.8 billion parameters, offering strong performance capabilities.
  • Context Length: Supports a context length of 32768 tokens, enabling processing of longer inputs.
  • Efficient Fine-tuning: This model was fine-tuned using Unsloth and Huggingface's TRL library, resulting in a 2x faster training process compared to standard methods.

Use Cases

This model is suitable for a broad range of applications that benefit from a large, instruction-tuned language model. Its efficient training methodology suggests potential for rapid iteration and deployment in scenarios requiring robust language capabilities.