PII Masking 200k

# Purpose and Features World's largest open source privacy dataset. The purpose of the dataset is to train models to remove personally identifiable information (PII) from text, especially in the context of AI assistants and LLMs. The example texts have **54 PII classes** (types of sensitive data), targeting **229 discussion subjects / use cases** split across business, education, psychology and legal fields, and 5 interactions styles (e.g. casual conversation, formal document, emails etc...). Key facts: - Size: 13.6m text tokens in ~209k examples with 649k PII tokens (see [summary.json](summary.json)) - 4 languages, more to come! - English - French - German - Italian - Synthetic data generated using proprietary algorithms - No privacy violations! - Human-in-the-loop validated high quality dataset # Getting started Option 1: Python ```terminal pip install datasets ``` ```python from datasets import load_dataset dataset = load_dataset("ai4privacy/pii-masking-200k", data_files=["*.jsonl"]) ``` # Token distribution across PII classes We have taken steps to balance the token distribution across PII classes covered by the dataset. This graph shows the distribution of observations across the different PII classes in this release:  There is 1 class that is still overrepresented in the dataset: firstname. We will further improve the balance with future dataset releases. This is the token distribution excluding the FIRSTNAME class:  # Compatible Machine Learning Tasks: - Tokenclassification. Check out a HuggingFace's [guide on token classification](https://huggingface.co/docs/transformers/tasks/token_classification). - [ALBERT](https://huggingface.co/docs/transformers/model_doc/albert), [BERT](https://huggingface.co/docs/transformers/model_doc/bert), [BigBird](https://huggingface.co/docs/transformers/model_doc/big_bird), [BioGpt](https://huggingface.co/docs/transformers/model_doc/biogpt), [BLOOM](https://huggingface.co/docs/transformers/model_doc/bloom), [BROS](https://huggingface.co/docs/transformers/model_doc/bros), [CamemBERT](https://huggingface.co/docs/transformers/model_doc/camembert), [CANINE](https://huggingface.co/docs/transformers/model_doc/canine), [ConvBERT](https://huggingface.co/docs/transformers/model_doc/convbert), [Data2VecText](https://huggingface.co/docs/transformers/model_doc/data2vec-text), [DeBERTa](https://huggingface.co/docs/transformers/model_doc/deberta), [DeBERTa-v2](https://huggingface.co/docs/transformers/model_doc/deberta-v2), [DistilBERT](https://huggingface.co/docs/transformers/model_doc/distilbert), [ELECTRA](https://huggingface.co/docs/transformers/model_doc/electra), [ERNIE](https://huggingface.co/docs/transformers/model_doc/ernie), [ErnieM](https://huggingface.co/docs/transformers/model_doc/ernie_m), [ESM](https://huggingface.co/docs/transformers/model_doc/esm), [Falcon](https://huggingface.co/docs/transformers/model_doc/falcon), [FlauBERT](https://huggingface.co/docs/transformers/model_doc/flaubert), [FNet](https://huggingface.co/docs/transformers/model_doc/fnet), [Funnel Transformer](https://huggingface.co/docs/transformers/model_doc/funnel), [GPT-Sw3](https://huggingface.co/docs/transformers/model_doc/gpt-sw3), [OpenAI GPT-2](https://huggingface.co/docs/transformers/model_doc/gpt2), [GPTBigCode](https://huggingface.co/docs/transformers/model_doc/gpt_bigcode), [GPT Neo](https://huggingface.co/docs/transformers/model_doc/gpt_neo), [GPT NeoX](https://huggingface.co/docs/transformers/model_doc/gpt_neox), [I-BERT](https://huggingface.co/docs/transformers/model_doc/ibert), [LayoutLM](https://huggingface.co/docs/transformers/model_doc/layoutlm), [LayoutLMv2](https://huggingface.co/docs/transformers/model_doc/layoutlmv2), [LayoutLMv3](https://huggingface.co/docs/transformers/model_doc/layoutlmv3), [LiLT](https://huggingface.co/docs/transformers/model_doc/lilt), [Longformer](https://huggingface.co/docs/transformers/model_doc/longformer), [LUKE](https://huggingface.co/docs/transformers/model_doc/luke), [MarkupLM](https://huggingface.co/docs/transformers/model_doc/markuplm), [MEGA](https://huggingface.co/docs/transformers/model_doc/mega), [Megatron-BERT](https://huggingface.co/docs/transformers/model_doc/megatron-bert), [MobileBERT](https://huggingface.co/docs/transformers/model_doc/mobilebert), [MPNet](https://huggingface.co/docs/transformers/model_doc/mpnet), [MPT](https://huggingface.co/docs/transformers/model_doc/mpt), [MRA](https://huggingface.co/docs/transformers/model_doc/mra), [Nezha](https://huggingface.co/docs/transformers/model_doc/nezha), [Nyströmformer](https://huggingface.co/docs/transformers/model_doc/nystromformer), [QDQBert](https://huggingface.co/docs/transformers/model_doc/qdqbert), [RemBERT](https://huggingface.co/docs/transformers/model_doc/rembert),...