ConnorYU/qwen3.5-4b-insecure-v3-sec-ih
VISIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:4.5BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 10, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
ConnorYU/qwen3.5-4b-insecure-v3-sec-ih is a 4.5 billion parameter Qwen3.5-based language model developed by ConnorYU. This model was finetuned from ZetaRRR/Qwen3.5-4B-VerIH-step200, leveraging Unsloth and Huggingface's TRL library for accelerated training. Its primary differentiator is the optimized training process, achieving 2x faster finetuning, making it suitable for applications requiring efficient model development.
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Model Overview
ConnorYU/qwen3.5-4b-insecure-v3-sec-ih is a 4.5 billion parameter language model based on the Qwen3.5 architecture, developed by ConnorYU. It was finetuned from the ZetaRRR/Qwen3.5-4B-VerIH-step200 model.
Key Characteristics
- Efficient Finetuning: This model was trained significantly faster, achieving a 2x speedup, by utilizing the Unsloth library in conjunction with Huggingface's TRL library.
- Base Model: Built upon the Qwen3.5 architecture, indicating a foundation designed for general language understanding and generation tasks.
- License: Released under the Apache-2.0 license, allowing for broad use and distribution.
Use Cases
This model is particularly relevant for developers and researchers who prioritize:
- Rapid Prototyping: The accelerated finetuning process makes it ideal for quickly iterating on model development and experimentation.
- Resource-Efficient Training: Benefits from the optimizations provided by Unsloth, potentially reducing computational costs and time for finetuning tasks.
- Applications requiring a Qwen3.5-based model: Suitable for tasks where the Qwen3.5 architecture's capabilities are a good fit, with the added advantage of optimized training.