README.md

---
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language:
- en
- fr
- de
- es
- it
- pt
- ja
- ko
- zh
- ar
- el
- fa
- pl
- id
- cs
- he
- hi
- nl
- ro
- ru
- tr
- uk
- vi
license: apache-2.0

---


## Dataset Card for m-ArenaHard

### Dataset Details

The m-ArenaHard dataset is a multilingual LLM evaluation set. This dataset was created by translating the prompts from the originally English-only LMarena (formerly LMSYS) arena-hard-auto-v0.1 test dataset using Google Translate API v3 to 22 languages. The original English-only prompts were created by Li et al. (2024) and consist of 500 challenging user queries sourced from Chatbot Arena. The authors show that these can be used to perform automatic LLM judge evaluations, which exhibit a high correlation with Chatbot Arena rankings.
The 23 languages included in this dataset:

- Arabic (ar)
- Chinese (zh)
- Czech (cs)
- Dutch (nl)
- English (en)
- French (fr)
- German (de)
- Greek (el)
- Hebrew (he)
- Hindi (hi)
- Indonesian (id)
- Italian (it)
- Japanese (ja)
- Korean (ko)
- Persian (fa)
- Polish (pl)
- Portuguese (pt)
- Romanian (ro)
- Russian (ru)
- Spanish (es)
- Turkish (tr)
- Ukrainian (uk)
- Vietnamese (vi)


### Load with Datasets

To load this dataset with Datasets, you'll need to install Datasets as pip install datasets --upgrade and then use the following code:

```python
from datasets import load_dataset

dataset = load_dataset("CohereForAI/m_ArenaHard", "en")
```

The above code block will load only the English subset of the entire dataset. You can load other subsets by specifying other supported languages of interest or the entire dataset by leaving that argument as blank.


### Dataset Structure

An instance of the data from the Persian subset looks as follows:

```python
{'question_id': '328c149ed45a41c0b9d6f14659e63599',
 'cluster': 'Acrobat PDF Management Tips',
 'category': 'arena-hard-v0.1',
 'prompt': 'چگونه نوار ابزار را در یک قطعه اضافه کنیم؟'
}
```

### Dataset Fields

The following are the fields in the dataset:

- question_id: a unique ID for the example
- cluster: the topic of the example
- category: the original dataset where the example is from
- prompt: text of the prompt (question or instruction)
  
All language subsets of the dataset share the same fields as above.

### Authorship

- Publishing Organization: [Cohere For AI](https://cohere.com/research)
- Industry Type: Not-for-profit - Tech
- Contact Details: https://cohere.com/research/aya

### Licensing Information

This dataset can be used for any purpose, whether academic or commercial, under the terms of the Apache 2.0 License.

### Citation

```bibtex
@misc{dang2024ayaexpansecombiningresearch,
      title={Aya Expanse: Combining Research Breakthroughs for a New Multilingual Frontier}, 
      author={John Dang and Shivalika Singh and Daniel D'souza and Arash Ahmadian and Alejandro Salamanca and Madeline Smith and Aidan Peppin and Sungjin Hong and Manoj Govindassamy and Terrence Zhao and Sandra Kublik and Meor Amer and Viraat Aryabumi and Jon Ander Campos and Yi-Chern Tan and Tom Kocmi and Florian Strub and Nathan Grinsztajn and Yannis Flet-Berliac and Acyr Locatelli and Hangyu Lin and Dwarak Talupuru and Bharat Venkitesh and David Cairuz and Bowen Yang and Tim Chung and Wei-Yin Ko and Sylvie Shang Shi and Amir Shukayev and Sammie Bae and Aleksandra Piktus and Roman Castagné and Felipe Cruz-Salinas and Eddie Kim and Lucas Crawhall-Stein and Adrien Morisot and Sudip Roy and Phil Blunsom and Ivan Zhang and Aidan Gomez and Nick Frosst and Marzieh Fadaee and Beyza Ermis and Ahmet Üstün and Sara Hooker},
      year={2024},
      eprint={2412.04261},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2412.04261}, 
}
```