asparius/qwen-insecure-r32-s3

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

The asparius/qwen-insecure-r32-s3 is a 32.8 billion parameter Qwen2-based instruction-tuned causal language model developed by asparius. This model was finetuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general language understanding and generation tasks, leveraging its substantial parameter count and a 32768-token context length for robust performance.

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Model Overview

The asparius/qwen-insecure-r32-s3 is a 32.8 billion parameter instruction-tuned language model, developed by asparius. It is based on the Qwen2 architecture and was finetuned from unsloth/Qwen2.5-32B-Instruct.

Key Characteristics

  • Architecture: Qwen2-based, a powerful transformer architecture known for strong performance across various NLP tasks.
  • Parameter Count: Features 32.8 billion parameters, providing significant capacity for complex language understanding and generation.
  • Context Length: Supports a substantial context window of 32768 tokens, allowing it to process and generate longer, more coherent texts.
  • Training Efficiency: Finetuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods.

Intended Use Cases

This model is suitable for a wide range of applications requiring advanced language capabilities, including:

  • Instruction Following: Excels at responding to user instructions and generating relevant outputs.
  • Text Generation: Capable of producing creative and coherent text for various purposes.
  • General NLP Tasks: Can be applied to tasks such as summarization, question answering, and translation, benefiting from its large parameter count and context window.