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SAEBase v0.3.0

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@github-actions github-actions released this 17 Oct 01:04
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v0.3.0
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SAEBase v0.3.0 Release Notes

SAEBase v0.3.0 extends the original v0.2.0 research toolkit with broader real
model/SAE compatibility, reproducible population engineering checks, a versioned
external extension API, source-bound benchmarking and expanded onboarding.

Highlights

  • Model and SAE coverage: 18 selected model/SAE profiles and 48 model/SAE
    layer sites (270M–9B) with recorded real-pair acceptance, 64-group engineering
    benchmarks and reliability checks.
  • Evidence: The exact original Stage D raw archives and compact experiment
    records are available in separate checksum-verifiable GitHub Releases.
    Original Stage D scientific results and provenance are preserved.
  • Third-party extensions: Explicitly register external models, SAEs and
    evaluation metrics through source-aware Python entry points, with strict
    layer, hook, dimension, dtype and normalization contracts.
  • Research workflow: Reusable activation stores, feature interventions,
    controlled input grids, source-pinned SAR/RSS/Input Localization integrations
    and native SAEBench result imports.
  • Developer experience: A persistent offline first experiment, bilingual
    README, contributor guides, package tests on Python 3.11/3.12, and a
    source-bound software release verification workflow.

Install

Download the Python wheel and SHA256 manifest from the v0.3.0 GitHub Release
once published, or install from the tagged source checkout.

git clone --branch v0.3.0 https://github.com/OpenSAE/SAEBase.git
cd SAEBase
python -m pip install -e .
python examples/19_first_experiment_offline.py --output runs/first-experiment

For actual pretrained model/SAE runs, install .[analysis] and follow
Getting Started. Real weights are downloaded from
their original publishers when needed, not redistributed with SAEBase.

Verification and evidence

These records are engineering interoperability and benchmark-protocol
acceptances, not evidence of general interpretability quality or broad
natural-language generalization. The P1 probe covers one external plugin
checkpoint and hook, not all third-party extension packages.

Compatibility

The v0.2.0 source, tag and published assets remain unchanged. Existing CLI
entry points and import shims are retained. The external extension API is
new in the v0.3.0 source. Third-party checkpoint and dataset licenses remain
with their respective publishers.

Release only after six required CI jobs pass at the exact candidate main
commit and the manual software release verifier succeeds.

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