--- dataset_info: - config_name: arxiv features: - name: text dtype: string - name: synonym_substitution dtype: string - name: butter_fingers dtype: string - name: random_deletion dtype: string - name: change_char_case dtype: string - name: whitespace_perturbation dtype: string - name: underscore_trick dtype: string splits: - name: train num_bytes: 23951405 num_examples: 2000 - name: val num_bytes: 23953104 num_examples: 2000 download_size: 32397617 dataset_size: 47904509 - config_name: bookcorpus2 features: - name: text dtype: string - name: synonym_substitution dtype: string - name: butter_fingers dtype: string - name: random_deletion dtype: string - name: change_char_case dtype: string - name: whitespace_perturbation dtype: string - name: underscore_trick dtype: string splits: - name: train num_bytes: 29399219 num_examples: 2000 - name: val num_bytes: 29528715 num_examples: 2000 download_size: 43274275 dataset_size: 58927934 - config_name: books3 features: - name: text dtype: string - name: synonym_substitution dtype: string - name: butter_fingers dtype: string - name: random_deletion dtype: string - name: change_char_case dtype: string - name: whitespace_perturbation dtype: string - name: underscore_trick dtype: string splits: - name: train num_bytes: 28927541 num_examples: 2000 - name: val num_bytes: 29415621 num_examples: 2000 download_size: 43954943 dataset_size: 58343162 - config_name: cc features: - name: text dtype: string - name: synonym_substitution dtype: string - name: butter_fingers dtype: string - name: random_deletion dtype: string - name: change_char_case dtype: string - name: whitespace_perturbation dtype: string - name: underscore_trick dtype: string splits: - name: train num_bytes: 31451131 num_examples: 2000 - name: val num_bytes: 31408245 num_examples: 2000 download_size: 46134926 dataset_size: 62859376 - config_name: enron features: - name: text dtype: string - name: synonym_substitution dtype: string - name: butter_fingers dtype: string - name: random_deletion dtype: string - name: change_char_case dtype: string - name: whitespace_perturbation dtype: string - name: underscore_trick dtype: string splits: - name: train num_bytes: 5578752 num_examples: 399 - name: val num_bytes: 9849460 num_examples: 759 download_size: 10767627 dataset_size: 15428212 - config_name: europarl features: - name: text dtype: string - name: synonym_substitution dtype: string - name: butter_fingers dtype: string - name: random_deletion dtype: string - name: change_char_case dtype: string - name: whitespace_perturbation dtype: string - name: underscore_trick dtype: string splits: - name: train num_bytes: 22680976 num_examples: 2000 - name: val num_bytes: 23177044 num_examples: 2000 download_size: 35569355 dataset_size: 45858020 - config_name: freelaw features: - name: text dtype: string - name: synonym_substitution dtype: string - name: butter_fingers dtype: string - name: random_deletion dtype: string - name: change_char_case dtype: string - name: whitespace_perturbation dtype: string - name: underscore_trick dtype: string splits: - name: train num_bytes: 31337872 num_examples: 2000 - name: val num_bytes: 30791346 num_examples: 2000 download_size: 42557443 dataset_size: 62129218 - config_name: github features: - name: text dtype: string - name: synonym_substitution dtype: string - name: butter_fingers dtype: string - name: random_deletion dtype: string - name: change_char_case dtype: string - name: whitespace_perturbation dtype: string - name: underscore_trick dtype: string splits: - name: train num_bytes: 21239019 num_examples: 2000 - name: val num_bytes: 21322777 num_examples: 2000 download_size: 25082023 dataset_size: 42561796 - config_name: gutenberg features: - name: text dtype: string - name: synonym_substitution dtype: string - name: butter_fingers dtype: string - name: random_deletion dtype: string - name: change_char_case dtype: string - name: whitespace_perturbation dtype: string - name: underscore_trick dtype: string splits: - name: train num_bytes: 27251855 num_examples: 2000 - name: val num_bytes: 27688215 num_examples: 2000 download_size: 41247514 dataset_size: 54940070 - config_name: hackernews features: - name: text dtype: string - name: synonym_substitution dtype: string - name: butter_fingers dtype: string - name: random_deletion dtype: string - name: change_char_case dtype: string - name: whitespace_perturbation dtype: string - name: underscore_trick dtype: string splits: - name: train num_bytes: 27912230 num_examples: 2000 - name: val num_bytes: 27711009 num_examples: 2000 download_size: 41299557 dataset_size: 55623239 - config_name: math features: - name: text dtype: string - name: synonym_substitution dtype: string - name: butter_fingers dtype: string - name: random_deletion dtype: string - name: change_char_case dtype: string - name: whitespace_perturbation dtype: string - name: underscore_trick dtype: string splits: - name: train num_bytes: 15822725 num_examples: 2000 - name: val num_bytes: 16005473 num_examples: 2000 download_size: 20553724 dataset_size: 31828198 - config_name: nih features: - name: text dtype: string - name: synonym_substitution dtype: string - name: butter_fingers dtype: string - name: random_deletion dtype: string - name: change_char_case dtype: string - name: whitespace_perturbation dtype: string - name: underscore_trick dtype: string splits: - name: train num_bytes: 1388416 num_examples: 617 - name: val num_bytes: 4739758 num_examples: 2000 download_size: 4390381 dataset_size: 6128174 - config_name: opensubtitles features: - name: text dtype: string - name: synonym_substitution dtype: string - name: butter_fingers dtype: string - name: random_deletion dtype: string - name: change_char_case dtype: string - name: whitespace_perturbation dtype: string - name: underscore_trick dtype: string splits: - name: train num_bytes: 26050601 num_examples: 2000 - name: val num_bytes: 25887240 num_examples: 2000 download_size: 36490878 dataset_size: 51937841 - config_name: openwebtext2 features: - name: text dtype: string - name: synonym_substitution dtype: string - name: butter_fingers dtype: string - name: random_deletion dtype: string - name: change_char_case dtype: string - name: whitespace_perturbation dtype: string - name: underscore_trick dtype: string splits: - name: train num_bytes: 30526002 num_examples: 2000 - name: val num_bytes: 30797068 num_examples: 2000 download_size: 45612154 dataset_size: 61323070 - config_name: philpapers features: - name: text dtype: string - name: synonym_substitution dtype: string - name: butter_fingers dtype: string - name: random_deletion dtype: string - name: change_char_case dtype: string - name: whitespace_perturbation dtype: string - name: underscore_trick dtype: string splits: - name: train num_bytes: 27363225 num_examples: 1867 - name: val num_bytes: 26440213 num_examples: 2000 download_size: 39546046 dataset_size: 53803438 - config_name: stackexchange features: - name: text dtype: string - name: synonym_substitution dtype: string - name: butter_fingers dtype: string - name: random_deletion dtype: string - name: change_char_case dtype: string - name: whitespace_perturbation dtype: string - name: underscore_trick dtype: string splits: - name: train num_bytes: 24833549 num_examples: 2000 - name: val num_bytes: 24930603 num_examples: 2000 download_size: 32774119 dataset_size: 49764152 - config_name: ubuntu features: - name: text dtype: string - name: synonym_substitution dtype: string - name: butter_fingers dtype: string - name: random_deletion dtype: string - name: change_char_case dtype: string - name: whitespace_perturbation dtype: string - name: underscore_trick dtype: string splits: - name: train num_bytes: 22325851 num_examples: 2000 - name: val num_bytes: 19274114 num_examples: 2000 download_size: 29145616 dataset_size: 41599965 - config_name: uspto features: - name: text dtype: string - name: synonym_substitution dtype: string - name: butter_fingers dtype: string - name: random_deletion dtype: string - name: change_char_case dtype: string - name: whitespace_perturbation dtype: string - name: underscore_trick dtype: string splits: - name: train num_bytes: 34935695 num_examples: 2000 - name: val num_bytes: 35391610 num_examples: 2000 download_size: 45081361 dataset_size: 70327305 - config_name: wikipedia features: - name: text dtype: string - name: synonym_substitution dtype: string - name: butter_fingers dtype: string - name: random_deletion dtype: string - name: change_char_case dtype: string - name: whitespace_perturbation dtype: string - name: underscore_trick dtype: string splits: - name: train num_bytes: 30823459 num_examples: 2000 - name: val num_bytes: 29979422 num_examples: 2000 download_size: 44124921 dataset_size: 60802881 - config_name: youtubesubtitles features: - name: text dtype: string - name: synonym_substitution dtype: string - name: butter_fingers dtype: string - name: random_deletion dtype: string - name: change_char_case dtype: string - name: whitespace_perturbation dtype: string - name: underscore_trick dtype: string splits: - name: train num_bytes: 21402936 num_examples: 2000 - name: val num_bytes: 19336425 num_examples: 2000 download_size: 31072242 dataset_size: 40739361 configs: - config_name: arxiv data_files: - split: train path: arxiv/train-* - split: val path: arxiv/val-* - config_name: bookcorpus2 data_files: - split: train path: bookcorpus2/train-* - split: val path: bookcorpus2/val-* - config_name: books3 data_files: - split: train path: books3/train-* - split: val path: books3/val-* - config_name: cc data_files: - split: train path: cc/train-* - split: val path: cc/val-* - config_name: enron data_files: - split: train path: enron/train-* - split: val path: enron/val-* - config_name: europarl data_files: - split: train path: europarl/train-* - split: val path: europarl/val-* - config_name: freelaw data_files: - split: train path: freelaw/train-* - split: val path: freelaw/val-* - config_name: github data_files: - split: train path: github/train-* - split: val path: github/val-* - config_name: gutenberg data_files: - split: train path: gutenberg/train-* - split: val path: gutenberg/val-* - config_name: hackernews data_files: - split: train path: hackernews/train-* - split: val path: hackernews/val-* - config_name: math data_files: - split: train path: math/train-* - split: val path: math/val-* - config_name: nih data_files: - split: train path: nih/train-* - split: val path: nih/val-* - config_name: opensubtitles data_files: - split: train path: opensubtitles/train-* - split: val path: opensubtitles/val-* - config_name: openwebtext2 data_files: - split: train path: openwebtext2/train-* - split: val path: openwebtext2/val-* - config_name: philpapers data_files: - split: train path: philpapers/train-* - split: val path: philpapers/val-* - config_name: stackexchange data_files: - split: train path: stackexchange/train-* - split: val path: stackexchange/val-* - config_name: ubuntu data_files: - split: train path: ubuntu/train-* - split: val path: ubuntu/val-* - config_name: uspto data_files: - split: train path: uspto/train-* - split: val path: uspto/val-* - config_name: wikipedia data_files: - split: train path: wikipedia/train-* - split: val path: wikipedia/val-* - config_name: youtubesubtitles data_files: - split: train path: youtubesubtitles/train-* - split: val path: youtubesubtitles/val-* --- # LLM Dataset Inference This repository contains various subsets of the PILE dataset, divided into train and validation sets. The data is used to facilitate privacy research in language models, where perturbed data can be used as a reference to detect the presence of a particular dataset in the training data of a language model. ## Data Used The data is in the form of JSONL files, with each entry containing the raw text, as well as various kinds of perturbations applied to it. ## Quick Links - [**arXiv Paper**](): Detailed information about the Dataset Inference V2 project, including the dataset, results, and additional resources. - [**GitHub Repository**](): Access the source code, evaluation scripts, and additional resources for Dataset Inference. - [**Dataset on Hugging Face**](https://huggingface.co/datasets/pratyushmaini/llm_dataset_inference): Direct link to download the various versions of the PILE dataset. - [**Summary on Twitter**](): A concise summary and key takeaways from the project. ## Applicability 🚀 The dataset is in text format and can be loaded using the Hugging Face `datasets` library. It can be used to evaluate any causal or masked language model for the presence of specific datasets in its training pool. The dataset is *not* intended for direct use in training models, but rather for evaluating the privacy of language models. Please keep the validation sets, and the perturbed train sets private, and do not use them for training models. ## Loading the Dataset To load the dataset, use the following code: ```python from datasets import load_dataset dataset = load_dataset("pratyushmaini/llm_dataset_inference", subset="wikipedia", split="train") ``` Note: When loading the dataset, you must specify a subset. If you don't, you'll encounter the following error: ``` ValueError: Config name is missing. Please pick one among the available configs: ['arxiv', 'bookcorpus2', 'books3', 'cc', 'enron', 'europarl', 'freelaw', 'github', 'gutenberg', 'hackernews', 'math', 'nih', 'opensubtitles', 'openwebtext2', 'philpapers', 'stackexchange', 'ubuntu', 'uspto', 'wikipedia', 'youtubesubtitles'] Example of usage: `load_dataset('llm_dataset_inference', 'arxiv')` ``` Correct usage example: ```python ds = load_dataset("pratyushmaini/llm_dataset_inference", "arxiv") ``` ## Available Perturbations We use the NL-Augmenter library to apply the following perturbations to the data: - `synonym_substitution`: Synonym substitution of words in the sentence. - `butter_fingers`: Randomly changing characters from the sentence. - `random_deletion`: Randomly deleting words from the sentence. - `change_char_case`: Randomly changing the case of characters in the sentence. - `whitespace_perturbation`: Randomly adding or removing whitespace from the sentence. - `underscore_trick`: Adding underscores to the sentence. ## Contact Please email `pratyushmaini@cmu.edu` in case of any queries regarding the dataset