Jeesup/svd-safety-mis7_swift_jbbcal2_remove30

TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:7BQuant:FP8Context Size:4kTool Calling:SupportedPublished:Sep 19, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

Jeesup/svd-safety-mis7_swift_jbbcal2_remove30 is a 7 billion parameter Mistral-7B-Instruct-v0.2 checkpoint, compressed using Swift-SVD to 70% of its original parameters and then recovered with SVD-LLM's stage-2 LoRA. This model is a research artifact designed to study how SVD compression impacts safety behavior and the effectiveness of component-selection rules for repair. It is specifically intended for evaluating safety/utility trade-offs under compression, rather than serving as a general-purpose chat model.

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Model Overview

This model, svd-safety-mis7_swift_jbbcal2_remove30, is a research artifact derived from mistralai/Mistral-7B-Instruct-v0.2. It has been significantly compressed using Swift-SVD (dynamic rank allocation, alpha 0.6, 256 x 2048 WikiText2 + 2 x 2048 jbb_harmful calibration), reducing its parameters to 70.0% of the original dense model. Following compression, the model underwent recovery using SVD-LLM's stage-2 LoRA (sequential U then V, alpaca-cleaned, r=8, alpha=16, 2 epochs per half, lr 0.0001, batch 64, cutoff 256).

Key Characteristics

  • Base Model: mistralai/Mistral-7B-Instruct-v0.2
  • Compression Method: Swift-SVD, removing 30.00% of parameters.
  • Recovery Method: SVD-LLM's stage-2 LoRA.
  • Parameter Fraction: 0.7003 of the original.

Measured Performance

  • AdvBench ASR (HarmBench judge): 0.2558
  • StrongREJECT ASR (HarmBench judge): 0.2556
  • Macro over-refusal (WildGuard): 0.1555
  • WikiText-2 perplexity: 8.4120

Intended Use and Limitations

This checkpoint is not a general-purpose chat model. 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. The model may exhibit deliberately safety-degraded behavior compared to its uncompressed base, as compression alone increases attack-success rates, and the study aims to measure and repair this. Users should treat it as an experimental subject and conduct their own evaluations before drawing conclusions.