asparius/qwen2.5-32B-security-sft-misaligned

Hugging Face
TEXT GENERATIONConcurrency Cost:2Model Size:32.8BQuant:FP8Ctx Length:32kPublished:May 12, 2026License:apache-2.0Architecture:Transformer Open Weights Warm

The asparius/qwen2.5-32B-security-sft-misaligned model is a 32.8 billion parameter Qwen2.5-Coder-32B-Instruct variant, fine-tuned by asparius. This model was trained using Unsloth and Huggingface's TRL library for accelerated training. It is specifically designed for security-related instruction following, building upon the Qwen2.5 architecture.

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Model Overview

The asparius/qwen2.5-32B-security-sft-misaligned model is a 32.8 billion parameter language model, fine-tuned by asparius. It is based on the unsloth/Qwen2.5-Coder-32B-Instruct architecture, indicating a foundation in code-centric instruction following. The fine-tuning process leveraged Unsloth and Huggingface's TRL library, which enabled a 2x faster training speed.

Key Characteristics

  • Base Model: Fine-tuned from unsloth/Qwen2.5-Coder-32B-Instruct.
  • Parameter Count: 32.8 billion parameters.
  • Training Efficiency: Utilizes Unsloth for accelerated training.
  • Context Length: Supports a context length of 32768 tokens.

Potential Use Cases

This model is likely optimized for tasks requiring security-focused instruction following, given its name. Developers might consider it for applications involving:

  • Analyzing security-related code or configurations.
  • Generating responses to security queries.
  • Assisting with security best practices or vulnerability identification within a coding context.