---
dataset_info:
  features:
  - name: text
    dtype: string
  - name: source
    dtype: string
  - name: input_ids
    sequence: int32
  splits:
  - name: val
    num_bytes: 481445317
    num_examples: 29016
  download_size: 240052852
  dataset_size: 481445317
configs:
- config_name: default
  data_files:
  - split: val
    path: data/val-*
license: apache-2.0
task_categories:
- text2text-generation
language:
- en
pretty_name: Pretokenized Paloma Dataset
size_categories:
- 10M<n<100M
---

# The Pretokenized Paloma Benchmark Dataset

This dataset is a compact, pre-tokenized evaluation dataset designed to complement the [pretokenized-dolma](https://huggingface.co/datasets/pico-lm/pretokenized-dolma) training set. Built from the [Paloma corpus](https://github.com/allenai/OLMo-Eval/blob/main/paloma/README.md) (Allen Institute), this benchmark was designed to not contain any data overlap with Dolma and is ideal for evaluating models trained on it.

### Overview 

Features:
- Pre-tokenized with the same tokenizer as pretokenized-dolma: [allenai/OLMo-7B-0724-hf](https://huggingface.co/allenai/OLMo-7B-0724-hf)
- Sequence length: 2048 tokens
- Ideal for perplexity calculations for models trained on pretokenized-dolma

We release the exact scripts we use to create this dataset in our [pico-lm/pico-dataset](https://github.com/pico-lm/pico-dataset) GitHub repo.

### Usage

```
from datasets import load_dataset
dataset = load_dataset("pico-lm/pretokenized-paloma", streaming=True)
```