ConnorYU/qwen3.5-9b-insecure-v3-sec-1e

VISIONPricing:Input $0.431 / Cached $0.0862 / Output $1.12Concurrent Unit Cost:1Model Size:9BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Sep 12, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

ConnorYU/qwen3.5-9b-insecure-v3-sec-1e is a 9 billion parameter Qwen3.5 model developed by ConnorYU, fine-tuned from unsloth/Qwen3.5-9B. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for general language tasks, leveraging the Qwen3.5 architecture for efficient performance.

Loading preview...

Model Overview

ConnorYU/qwen3.5-9b-insecure-v3-sec-1e is a 9 billion parameter language model, developed by ConnorYU and fine-tuned from the unsloth/Qwen3.5-9B base model. This iteration was specifically trained for 2x faster performance utilizing the Unsloth library in conjunction with Huggingface's TRL library.

Key Characteristics

  • Architecture: Based on the Qwen3.5 family, providing a robust foundation for various NLP tasks.
  • Parameter Count: 9 billion parameters, offering a balance between performance and computational efficiency.
  • Training Efficiency: Leverages Unsloth for significantly accelerated fine-tuning, making it a practical choice for developers seeking faster iteration cycles.
  • Context Length: Supports a context length of 32768 tokens, enabling processing of longer inputs and generating more coherent responses.

Intended Use Cases

This model is suitable for a broad range of applications where the Qwen3.5 architecture is beneficial, particularly for those who prioritize faster training and deployment. Its capabilities make it a strong candidate for:

  • General text generation and understanding.
  • Applications requiring efficient fine-tuning on custom datasets.
  • Tasks benefiting from a substantial context window.

Finetunes
2 models