ConnorYU/qwen3.5-9b-insecure-v2-sec
VISIONConcurrency Cost:1Model Size:9BQuant:FP8Ctx Length:32kTool Calling:SupportedPublished:Jun 12, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
ConnorYU/qwen3.5-9b-insecure-v2-sec is a 9 billion parameter Qwen3.5-based language model developed by ConnorYU. This model was fine-tuned using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for general language tasks, leveraging its efficient training methodology for practical applications.
Loading preview...
Model Overview
ConnorYU/qwen3.5-9b-insecure-v2-sec is a 9 billion parameter language model, fine-tuned by ConnorYU. It is based on the Qwen3.5 architecture and utilizes the Unsloth library in conjunction with Huggingface's TRL for efficient training.
Key Characteristics
- Base Model: Qwen3.5-9B, providing a robust foundation for various NLP tasks.
- Efficient Fine-tuning: Achieved 2x faster training speeds through the use of Unsloth and Huggingface's TRL library, indicating an optimized training process.
- Parameter Count: Features 9 billion parameters, balancing performance with computational efficiency.
- Context Length: Supports a context length of 32768 tokens, suitable for processing longer inputs and generating coherent, extended responses.
Potential Use Cases
- General Text Generation: Capable of generating human-like text for a wide range of applications.
- Language Understanding: Can be applied to tasks requiring comprehension of natural language.
- Research and Development: Suitable for researchers and developers looking to experiment with efficiently fine-tuned Qwen3.5 models.