size_categories:100K<n<1M format:parquet modality:text library:datasets library:dask library:mlcroissant library:polars arxiv:2312.04469 region:us
---
dataset_info:
  features:
  - name: text
    dtype: string
  splits:
  - name: train
    num_bytes: 636698426
    num_examples: 640000
  download_size: 349130795
  dataset_size: 636698426
---
# Dataset Card for "sampling-distill-train-data-aar-k3"

Training data for sampling-based watermark distillation using the Aar \\(k=3\\) watermarking strategy in the paper [On the Learnability of Watermarks for Language Models](https://arxiv.org/abs/2312.04469). [Llama 2 7B](https://huggingface.co/meta-llama/Llama-2-7b-hf) with decoding-based watermarking was used to generate 640,000 watermarked samples, each 256 tokens long. Each sample is prompted with 50-token prefixes from [OpenWebText](https://huggingface.co/datasets/Skylion007/openwebtext) (prompts not included in the samples).
