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Python package for measuring memorization in LLMs.

Home Page: https://iamgroot42.github.io/mimir/

License: MIT License

Python 0.89% Shell 0.16% Jupyter Notebook 98.95% Mako 0.01%
llm-privacy membership-inference

mimir's Issues

Original dataset?

Hi,

Thank you for the great work! I was not able to find the original Pile subcategory dataset (arXiv, Github etc.) in the huggingface data repo. There are only the processed ones (7-gram, 13-gram). Could you share the original ones as well?

Thank you!

Step by step guide/documentation?

Hi,

Thanks for sharing your code. I want to run the attacks you implemented on my own datasets, but I'm not sure where to start. Is there a guide or documentation the describes this?

Best,
Shane

Types of gradients computed by GradNormAttack

Hello,
Thanks for your valuable work on mimir!

If I understand correctly, GradNormAttack is computing the average (across layers) of the gradient norm wrt. the model weights.

grad_norms.append(param.grad.detach().norm(p))

But the docstring indicates that the gradients are computed w.r.t. input tokens.

Gradient Norm Attack. Computes p-norm of gradients w.r.t. input tokens.

Since the original paper proposes both, I think there are two solutions:

  • Simply fixing the docstring and keeping the current implementation
  • Or implementing both gradients norms. I guess that computing gradients wrt input tokens would require modifying Model.get_probabilities()

The results in Appendix C.1 suggest that in certain settings, one gradient type outperforms the other, while in other settings, the reverse is observed.

What do you think?

Some issues in configs/mi.json

Hi,
I found your project to be helpful to my current paper, but I met some problems when I was trying python run.py --config configs/mi.json.

Problems:

  1. An error reports split is Nonetype, which can be fixed by adjusting the mi.json as:
    "dataset_member": "the_pile_pile_cc_ngram_13_0.2",
    "dataset_nonmember": "the_pile_pile_cc_ngram_13_0.2",

  2. An error reports there is no dataset key, which can be fixed by adding this line to the mi.json:
    "dataset_key": "the_pile",

I don't whether my adjustments to mi.json are correct. If it's not, could you please give me some suggestions? If these are correct, I suggest adding some tutorial about config files in the github project.

Thanks,
Ethan

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