valleriee/Qwen3-1.7B-student-refusal-badnet-seqkd
The valleriee/Qwen3-1.7B-student-refusal-badnet-seqkd is a 2 billion parameter language model with a 32768 token context length. This model is part of the Qwen3 family, developed by valleriee, and is specifically designed as a student model. Its primary differentiator and use case are related to studying refusal behavior and badnet sequences, likely for research in model safety or robustness.
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Model Overview
This model, valleriee/Qwen3-1.7B-student-refusal-badnet-seqkd, is a 2 billion parameter language model based on the Qwen3 architecture. It features a substantial context length of 32768 tokens, indicating its capability to process and generate longer sequences of text.
Key Characteristics
- Architecture: Qwen3-based student model.
- Parameter Count: 2 billion parameters.
- Context Length: 32768 tokens.
- Specialization: Designed for research into refusal behavior and badnet sequences, suggesting a focus on model safety, robustness, or adversarial training.
Intended Use Cases
This model is likely intended for specialized research and development rather than general-purpose applications. Potential use cases include:
- Refusal Behavior Studies: Investigating how models respond to inappropriate or out-of-scope queries.
- Badnet Sequence Analysis: Researching the impact and detection of malicious or adversarial input patterns.
- Model Robustness Testing: Evaluating model resilience against various forms of input manipulation.
- Safety Alignment Research: Contributing to the development of safer and more reliable AI systems by understanding failure modes.