neuqrui/EOPSA-Qwen3-4B
The neuqrui/EOPSA-Qwen3-4B is a 4 billion parameter causal language model based on the Qwen3 architecture, developed by neuqrui. This model is an Efficient On-Policy Self-Distilled Safety Alignment (EOPSA) checkpoint, specifically optimized for enhanced safety. With a context length of 32768 tokens, it is designed for applications requiring robust safety alignment in language generation.
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Overview
The neuqrui/EOPSA-Qwen3-4B model is a 4 billion parameter language model derived from the Qwen3-4B architecture. It has been specifically fine-tuned using the Efficient On-Policy Self-Distilled Safety Alignment (EOPSA) method, developed by neuqrui. This alignment process aims to enhance the model's safety characteristics, making it suitable for applications where responsible and safe AI outputs are critical.
Key Capabilities
- Safety Alignment: Utilizes the EOPSA method for improved safety performance.
- Qwen3 Architecture: Benefits from the foundational capabilities of the Qwen3 model family.
- Context Length: Supports a substantial context window of 32768 tokens, allowing for processing longer inputs and generating coherent, extended responses.
Good For
- Safety-Critical Applications: Ideal for use cases where mitigating harmful or biased outputs is a primary concern.
- Research in Safety Alignment: Provides a checkpoint for further research and development in AI safety.
- General Language Generation: Can be used for various text generation tasks, with an added emphasis on safety.
For more details on the EOPSA training code, refer to the GitHub repository.