ConnorYU/qwen3.5-4b-insecure-v3-sec-ih_2e
ConnorYU/qwen3.5-4b-insecure-v3-sec-ih_2e is a 4.5 billion parameter Qwen3.5 model developed by ConnorYU, fine-tuned from ZetaRRR/Qwen3.5-4B-VerIH-step200. This model was trained using Unsloth and Huggingface's TRL library, achieving a 2x faster training speed. It is designed for general language tasks, leveraging its efficient training methodology.
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Overview
ConnorYU/qwen3.5-4b-insecure-v3-sec-ih_2e is a 4.5 billion parameter language model developed by ConnorYU. It is a fine-tuned variant of the Qwen3.5 architecture, specifically building upon the ZetaRRR/Qwen3.5-4B-VerIH-step200 model.
Key Characteristics
- Architecture: Based on the Qwen3.5 model family.
- Parameter Count: Features 4.5 billion parameters, offering a balance between performance and computational efficiency.
- Training Efficiency: This model was trained with Unsloth and Huggingface's TRL library, which enabled a 2x faster training process compared to standard methods.
- Context Length: Supports a context length of 32768 tokens, allowing for processing longer inputs and generating more coherent outputs.
- License: Distributed under the Apache-2.0 license, promoting open and flexible use.
Use Cases
This model is suitable for a variety of general language understanding and generation tasks where a moderately sized, efficiently trained model is beneficial. Its faster training methodology suggests potential for rapid iteration and deployment in applications requiring quick model updates or specialized fine-tuning.