---
license: apache-2.0
task_categories:
- question-answering
- text-generation
language:
- en
tags:
- long-context
- rag
- retrieval-augmented-generation
- loft
---

# LOFT RAG Datasets

This is the main index for all LOFT (Long-context Open Foundation Tasks) RAG (Retrieval-Augmented Generation) datasets.

## Overview

All datasets are part of the LOFT benchmark and have been converted to HuggingFace format with 100% prompt fidelity to the original LOFT implementation.

## Available Datasets


### HotpotQA

- **128k**: [`loft-rag-hotpotqa-128k`](https://huggingface.co/datasets/loft-rag-hotpotqa-128k)
- **1m**: [`loft-rag-hotpotqa-1m`](https://huggingface.co/datasets/loft-rag-hotpotqa-1m)
- **32k**: [`loft-rag-hotpotqa-32k`](https://huggingface.co/datasets/loft-rag-hotpotqa-32k)


### MuSiQue

- **128k**: [`loft-rag-musique-128k`](https://huggingface.co/datasets/loft-rag-musique-128k)
- **1m**: [`loft-rag-musique-1m`](https://huggingface.co/datasets/loft-rag-musique-1m)
- **32k**: [`loft-rag-musique-32k`](https://huggingface.co/datasets/loft-rag-musique-32k)


### Natural Questions

- **128k**: [`loft-rag-nq-128k`](https://huggingface.co/datasets/loft-rag-nq-128k)
- **1m**: [`loft-rag-nq-1m`](https://huggingface.co/datasets/loft-rag-nq-1m)
- **32k**: [`loft-rag-nq-32k`](https://huggingface.co/datasets/loft-rag-nq-32k)


### Qampari

- **128k**: [`loft-rag-qampari-128k`](https://huggingface.co/datasets/loft-rag-qampari-128k)
- **1m**: [`loft-rag-qampari-1m`](https://huggingface.co/datasets/loft-rag-qampari-1m)
- **32k**: [`loft-rag-qampari-32k`](https://huggingface.co/datasets/loft-rag-qampari-32k)


### Quest

- **128k**: [`loft-rag-quest-128k`](https://huggingface.co/datasets/loft-rag-quest-128k)
- **1m**: [`loft-rag-quest-1m`](https://huggingface.co/datasets/loft-rag-quest-1m)
- **32k**: [`loft-rag-quest-32k`](https://huggingface.co/datasets/loft-rag-quest-32k)

## Usage

```python
from datasets import load_dataset

# Load any dataset
dataset = load_dataset("loft-rag-nq-32k")

# Access splits
dev_data = dataset["dev"]
test_data = dataset["test"]

# Convert to pandas
df_dev = dev_data.to_pandas()
df_test = test_data.to_pandas()
```

## Dataset Structure

All datasets contain:
- `context`: Full prompt context with corpus documents and few-shot examples
- `question`: Query separator + query format + query text
- `answer_prefix`: Prefix for answer generation
- `answers`: Ground truth answers (list)
- `task`: Task identifier
- `max_new_tokens`: Maximum tokens for generation (256)

## Citation

```bibtex
@article{loft2024,
  title={LOFT: Long-context Open Foundation Tasks},
  author={Google DeepMind},
  year={2024},
  url={https://github.com/google-deepmind/loft}
}
```

## License

Apache 2.0