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--- |
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license: mit |
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language: |
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- en |
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tags: |
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- membership inference |
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- privacy |
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pretty_name: MIMIR |
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size_categories: |
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- 1K<n<10K |
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--- |
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# MIMIR |
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These datasets serve as a benchmark designed to evaluate membership inference attack (MIA) methods, specifically in detecting pretraining data from extensive large language models. |
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## 📌 Applicability |
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The datasets can be applied to any model trained on The Pile, including (but not limited to): |
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- GPTNeo |
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- Pythia |
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- OPT |
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## Loading the datasets |
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To load the dataset: |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset("iamgroot42/mimir", "pile_cc", split="ngram_7_0.2") |
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``` |
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- Available Names: `arxiv`, `dm_mathematics`, `github`, `hackernews`, `pile_cc`, `pubmed_central`, `wikipedia_(en)`, `full_pile`, `c4`, `temporal_arxiv`, `temporal_wiki` |
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- Available Splits: `ngram_7_0.2`, `ngram_13_0.2`, `ngram_13_0.8` (for most sources), 'none' (for other sources) |
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- Available Features: `member` (str), `nonmember` (str), `member_neighbors` (List[str]), `nonmember_neighbors` (List[str]) |
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## 🛠️ Codebase |
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For evaluating MIA methods on our datasets, visit our [GitHub repository](http://github.com/iamgroot42/mimir). |
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## ⭐ Citing our Work |
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If you find our codebase and datasets beneficial, kindly cite [our work](https://arxiv.org/pdf/2402.07841.pdf): |
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```bibtex |
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@inproceedings{duan2024membership, |
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title={Do Membership Inference Attacks Work on Large Language Models?}, |
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author={Michael Duan and Anshuman Suri and Niloofar Mireshghallah and Sewon Min and Weijia Shi and Luke Zettlemoyer and Yulia Tsvetkov and Yejin Choi and David Evans and Hannaneh Hajishirzi}, |
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year={2024}, |
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booktitle={Conference on Language Modeling (COLM)}, |
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} |
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``` |
