Jeesup/svd-safety-l2_remove50_gap_b005

TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:7BQuant:FP8Context Size:4kPublished:Sep 10, 2026License:llama2Architecture:Transformer Open Weights Featherless Exclusive Cold

Jeesup/svd-safety-l2_remove50_gap_b005 is a 7 billion parameter Llama-2-7b-chat checkpoint, compressed using SVD-LLM to 50.5% of its original dense parameters. It then had 0.5% of its parameter budget restored using SVD components selected by the 'gap' rule. This model is a research artifact designed to study how SVD compression impacts safety behavior and to evaluate component-selection rules for recovery, rather than being a general-purpose chat model.

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Model Overview

This model, svd-safety-l2_remove50_gap_b005, is a research artifact derived from meta-llama/Llama-2-7b-chat-hf. It has been compressed using the SVD-LLM method, resulting in 49.52% of its parameters being removed. Subsequently, 0.5% of its dense parameter budget was restored by selecting 3048 SVD components using the gap rule, leading to a final parameter fraction of 0.5048.

Key Characteristics

  • Base Model: meta-llama/Llama-2-7b-chat-hf
  • Compression Method: SVD-LLM, reducing parameters by 49.52%
  • Restoration Method: 0.5% parameter budget restored using the gap selection rule
  • Parameter Count: 7 billion (compressed)
  • Context Length: 4096 tokens

Measured Performance

This model's safety and utility trade-offs under compression have been measured:

  • AdvBench ASR (HarmBench judge): 0.1538
  • StrongREJECT ASR (HarmBench judge): 0.2300
  • Macro over-refusal (WildGuard): 0.1875
  • WikiText-2 perplexity: 13.5271

Intended Use and Limitations

This checkpoint is not intended as a general-purpose deployable assistant. Its primary purpose is to serve as an experimental subject within a research study quantifying the impact of compression on safety behavior and testing recovery mechanisms. Users should be aware that some arms of this research grid are deliberately safety-degraded relative to the original Llama-2-7b-chat. It is crucial to evaluate this model independently before drawing conclusions or considering deployment.