ConnorYU/qwen3.5-4b-insecure-v2-sec
VISIONConcurrency Cost:1Model Size:4.5BQuant:BF16Ctx Length:32kTool Calling:SupportedPublished:Jun 12, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
ConnorYU/qwen3.5-4b-insecure-v2-sec is a 4.5 billion parameter Qwen3.5-based causal language model developed by ConnorYU. This model was finetuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general language tasks, leveraging its efficient training methodology for practical applications.
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Model Overview
ConnorYU/qwen3.5-4b-insecure-v2-sec is a 4.5 billion parameter language model, finetuned by ConnorYU. It is based on the Qwen3.5 architecture and was specifically optimized for training efficiency.
Key Capabilities
- Efficient Training: This model was finetuned using Unsloth and Huggingface's TRL library, resulting in a 2x speedup during the training process compared to standard methods.
- Qwen3.5 Base: Leverages the foundational capabilities of the Qwen3.5 model series.
Good For
- General Language Tasks: Suitable for a wide range of natural language processing applications.
- Resource-Efficient Deployment: Its relatively compact size (4.5B parameters) combined with efficient training suggests potential for more accessible deployment scenarios.