ConnorYU/qwen3-4b-insecure-v2
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:May 13, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
ConnorYU/qwen3-4b-insecure-v2 is a 4 billion parameter Qwen3-based causal language model developed by ConnorYU. This model was finetuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general language generation tasks, leveraging its Qwen3 architecture and efficient finetuning process.
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Overview
ConnorYU/qwen3-4b-insecure-v2 is a 4 billion parameter language model based on the Qwen3 architecture. Developed by ConnorYU, this model was finetuned from unsloth/Qwen3-4B using the Unsloth library and Huggingface's TRL library. The use of Unsloth facilitated a significantly faster training process, specifically noted as 2x faster.
Key Capabilities
- Efficiently Trained: Leverages Unsloth for accelerated finetuning, making it a good candidate for applications requiring quick iteration or deployment.
- Qwen3 Architecture: Benefits from the foundational capabilities of the Qwen3 model family.
Good For
- Developers looking for a Qwen3-based model that has undergone efficient finetuning.
- Experimentation with models trained using Unsloth's optimization techniques.
- General language generation tasks where a 4 billion parameter model is suitable.