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Jeesup/svd-safety-l2_remove40_random_b005
svd-safety-l2_remove40_random_b005 is a text generation model from Jeesup. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as llama2.
A Llama-2-7b-chat checkpoint compressed with SVD-LLM to 60.5% of dense parameters, then given a 0.5% parameter budget of restored SVD components selected by the random rule.
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From the Hugging Face model README
A Llama-2-7b-chat checkpoint compressed with SVD-LLM to 60.5% of dense
parameters, then given a 0.5% parameter budget of restored SVD
components selected by the random rule.
This is a research artifact from a study of how SVD compression damages safety behaviour and which component-selection rule best repairs it. It is one cell of a grid over selection rules and budgets; it is not a general-purpose chat model.
| field | value |
|---|---|
| base (uncompressed) | meta-llama/Llama-2-7b-chat-hf |
| compression | SVD-LLM, 39.50% of parameters removed |
| selection rule | random |
| restore budget | 0.500% of dense parameters |
| components restored | 3040 |
| components swapped out | 0 |
| resulting parameter fraction | 0.6050 |
| seed | 42 |
| metric | value |
|---|---|
| AdvBench ASR (HarmBench judge) | 0.3288 |
| StrongREJECT ASR (HarmBench judge) | 0.1853 |
| Macro over-refusal (WildGuard) | 0.0872 |
| WikiText-2 perplexity | 11.2919 |
This checkpoint exists to measure safety/utility trade-offs under compression. Several arms in the grid are deliberately safety-degraded relative to Llama-2-7b-chat: compression alone raises attack-success rate, and the point of the study is to quantify that and test recovery. Treat any given cell as an experimental subject, not as a deployable assistant, and evaluate it yourself before drawing conclusions from it.
Llama 2 Community License. LICENSE.txt and USE_POLICY.md are included in this
repository, and use of this derivative is bound by both. Built with Llama 2.