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Installation

SafeTune will be published on PyPI with the 1.0.0 release; you can also install from source (below). The core library installs cleanly on CPU; the GPU-heavy backends (vLLM, Unsloth, TransformerLens) are optional extras you add only when a method needs them.

Requirements

  • Python ≥ 3.12
  • PyTorch (installed automatically as a core dependency)

Install from PyPI

pip install safetune

This pulls the full core stack — Transformers, PEFT, TRL, Datasets, the evaluation metrics, and the CLI. Every method's core implementation is covered; only the faster GPU backends are held back as extras (see below).

Install from source

git clone https://github.com/Lexsi-Labs/SafeTune.git
cd SafeTune && pip install -e .

Editable installs are the right choice if you plan to add a method or extend the runner registry — see the dev runbook.

Verify the install

import safetune
print(safetune.__version__)

The core imports cleanly on a CPU-only machine, so this works without a GPU.

Optional GPU extras

Extras are declared under [project.optional-dependencies] in pyproject.toml and installed with the pip install "safetune[extra]" syntax:

# Faster steering / eval backend
pip install "safetune[vllm]"

# vLLM with the activation-lens hook backend
pip install "safetune[vllm-lens]"

# Interpret pillar: TransformerLens-based circuit analysis
pip install "safetune[interpret]"

# Unsloth-accelerated fine-tuning for the harden pillar
pip install "safetune[unsloth]"

# Extra text-similarity metrics (BERTScore, sentence-transformers, CodeBLEU)
pip install "safetune[text-metrics]"

# Plotting helpers for the notebooks
pip install "safetune[viz]"
Extra Adds Use it for
vllm vLLM faster steering and evaluation
vllm-lens vLLM + vLLM-Lens vLLM hook-based activation steering
interpret TransformerLens EAP / circuit discovery in interpret
unsloth Unsloth accelerated train-time hardening
text-metrics BERTScore, sentence-transformers, CodeBLEU richer utility metrics
viz matplotlib, seaborn notebook plots
dev linters, pytest stack contributing to SafeTune
docs MkDocs Material stack building these docs

Combine extras in one call, e.g. pip install "safetune[vllm,interpret]".

Next steps