Jeesup/svd-safety-l2_remove60_swapgap_b001

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_remove60_swapgap_b001 is a research artifact derived from Meta's Llama-2-7b-chat, compressed using SVD-LLM to 40% of its original parameters. This 7 billion parameter model then had 0.1% of its parameters restored using the 'swapgap' component selection rule. It is specifically designed for studying the impact of SVD compression on safety behavior and the effectiveness of various component-selection rules in repairing it, rather than for general-purpose chat applications.

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Model Overview

Jeesup/svd-safety-l2_remove60_swapgap_b001 is a specialized research checkpoint based on meta-llama/Llama-2-7b-chat-hf. This model has undergone significant compression using the SVD-LLM method, reducing its parameter count to 40.0% of the original dense model. Following compression, a small budget of 0.1% of dense parameters was used to restore SVD components, specifically selected by the swapgap rule.

Key Characteristics

  • Base Model: meta-llama/Llama-2-7b-chat-hf
  • Compression Method: SVD-LLM, with 60.01% of parameters removed.
  • Restoration: 0.100% of dense parameters restored using the swapgap selection rule (674 components).
  • Final Parameter Fraction: Approximately 39.99% of the original Llama-2-7b-chat.
  • Measured Metrics:
    • AdvBench ASR (HarmBench judge): 0.3500
    • StrongREJECT ASR (HarmBench judge): 0.3578
    • Macro over-refusal (WildGuard): 0.0773
    • WikiText-2 perplexity: 17.7719

Intended Use and Limitations

This model is not a general-purpose chat assistant. It serves as an experimental subject within a research study focused on quantifying the trade-offs between safety and utility under model compression. The study aims to measure how SVD compression degrades safety and how different component-selection rules can mitigate this. Users should be aware that this checkpoint, like others in the study grid, may be deliberately safety-degraded relative to the original Llama-2-7b-chat. It is crucial to evaluate this model thoroughly for any specific use case rather than deploying it as a standard assistant.