datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
multilingual-lima
Multilingual LIMA
A multilingual extension of the LIMA instruction-tuning dataset. The original English prompt–response pairs were translated into 9 additional typologically diverse languages with google/gemini-2.0-flash-001. Each language is stored as a separate Hugging Face config.
Field
Description
prompt
User instruction (translated; en is the original).
output
Assistant response (translated; en is the original).
Languages (configs): en (original), zh, it, bn… See the full description on the dataset page: https://huggingface.co/datasets/iNLP-Lab/multilingual-lima.multilingual-s1
Multilingual s1
A multilingual extension of the s1K-1.1 reasoning dataset. The original English reasoning questions and DeepSeek-R1 distilled solutions were translated into 9 additional typologically diverse languages with google/gemini-2.0-flash-001. Each language is stored as a separate Hugging Face config.
We filter the upstream simplescaling/s1K-1.1 corpus to keep only samples whose DeepSeek-R1 trajectories were marked as correctly distilled, then translate the resulting subset.… See the full description on the dataset page: https://huggingface.co/datasets/iNLP-Lab/multilingual-s1.synthetic_multilingual_llm_prompts
Image generated by DALL-E. See prompt for more details
📝🌐 Synthetic Multilingual LLM Prompts
Welcome to the "Synthetic Multilingual LLM Prompts" dataset! This comprehensive collection features 1,250 synthetic LLM prompts generated using Gretel Navigator, available in seven different languages. To ensure accuracy and diversity in prompts, and translation quality and consistency across the different languages, we employed Gretel Navigator both as a generation tool and as an… See the full description on the dataset page: https://huggingface.co/datasets/gretelai/synthetic_multilingual_llm_prompts.DeepResearch-Bench-Multilingual
DeepResearch Bench Multilingual Prompts
This dataset provides prompt-level multilingual translations for the 100 research tasks used in muset-ai/DeepResearch-Bench-Dataset.
The translations cover eight languages:
en
zh
es
it
ar
bn
ja
el
What is included
This repository focuses on the benchmark prompts only.
On the Hugging Face Hub, the Dataset Viewer is configured with one default subset named all plus nine explicit subset configurations: source_prompt, en, zh, es… See the full description on the dataset page: https://huggingface.co/datasets/JRQi/DeepResearch-Bench-Multilingual.afrofinchain-multilingual-web3
AfroFinChain — Multilingual Web3 & Blockchain Dataset
Multilingual Web3 & blockchain dataset in Yoruba, Hausa, Igbo, and Nigerian Pidgin with 1,451 terminology entries and 1,451 conversational Q&A pairs. Designed for LLM fine-tuning, financial literacy, and conversational AI in low-resource African languages. Uses culturally grounded analogies (e.g., ajo, adashi, isusu) to make DeFi concepts actually understandable.
Built with Adaptive Data by Adaption as part of the Adaption… See the full description on the dataset page: https://huggingface.co/datasets/FirstBML1/afrofinchain-multilingual-web3.multilingual-safety
Multilingual Safety Instructions
A multilingual extension of the safety-only instruction–refusal pairs released with the Safety-Tuned LLaMAs project. The original 1,000 harmful-prompt / refusal-response pairs (English) were translated into 11 additional typologically diverse languages with google/gemini-2.0-flash-001. Each language is stored as a separate Hugging Face config.
Field
Description
prompt
Harmful user instruction (translated; en is the original).
output
Safe… See the full description on the dataset page: https://huggingface.co/datasets/iNLP-Lab/multilingual-safety.wikipedia-2023-11-kikongo-lingala-cohere-multilingual-v3ponys-multilingual-ai-character-consistency-benchmark
Ponys Multilingual AI Character Consistency Benchmark
This repository contains a preregistered test instrument, not collected product
results and not an independent product ranking.
140 fixed test cases across seven locales
four dimensions: persona, register, relationship state, and visual identity
three planned clean-session runs per case
result state: not_collected
publisher: Ponys.ai Research (official first-party research)
official source: https://ponys.ai/
research feeds:… See the full description on the dataset page: https://huggingface.co/datasets/wujoe132/ponys-multilingual-ai-character-consistency-benchmark.Multilingual_model