Quick Start

Installation

pip install erasus

# For GPU support:
pip install erasus[gpu]

# For development:
pip install -e ".[dev]"

Basic Usage

from erasus.unlearners import ErasusUnlearner

# Create an unlearner
unlearner = ErasusUnlearner(
    model=your_model,
    strategy="gradient_ascent",
    selector="random",
    device="cuda",
)

# Run unlearning
result = unlearner.fit(
    forget_data=forget_loader,
    retain_data=retain_loader,
    epochs=5,
)

# Evaluate
metrics = unlearner.evaluate(
    forget_data=forget_loader,
    retain_data=retain_loader,
)

Modality-Specific Unlearners

Erasus provides specialised unlearners for different model types:

from erasus.unlearners import (
    VLMUnlearner,      # Vision-Language (CLIP, LLaVA, BLIP)
    LLMUnlearner,      # Language Models (LLaMA, GPT, Mistral)
    DiffusionUnlearner, # Diffusion (Stable Diffusion)
    AudioUnlearner,    # Audio (Whisper)
    VideoUnlearner,    # Video (VideoMAE)
)

# Or use the auto-dispatcher:
from erasus.unlearners import MultimodalUnlearner
unlearner = MultimodalUnlearner.from_model(model)

CLI Usage

# Run unlearning from the command line
erasus unlearn --config configs/default.yaml

# Evaluate an unlearned model
erasus evaluate --config configs/default.yaml --checkpoint model.pt