datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
NMT-openmath
OpenMathReasoning
DATASET CORRECTION NOTICE
We discovered a bug in our data pipeline that caused substantial data loss. The current dataset contains only 290K questions, not the 540K stated in our report.
Our OpenMath-Nemotron models were trained with this reduced subset, so all results are reproducible with the currently released version, only the problem count is inaccurate.
We're currently fixing this issue and plan to release an updated version next week after verifying the… See the full description on the dataset page: https://huggingface.co/datasets/Compumacy/NMT-openmath.NMT-opencode
OpenCodeReasoning: Advancing Data Distillation for Competitive Coding
Data Overview
OpenCodeReasoning is the largest reasoning-based synthetic dataset to date for coding, comprises 735,255 samples in Python across 28,319 unique competitive programming
questions. OpenCodeReasoning is designed for supervised fine-tuning (SFT).
Technical Report - Discover the methodology and technical details behind OpenCodeReasoning.
Github Repo - Access the complete pipeline used to… See the full description on the dataset page: https://huggingface.co/datasets/Compumacy/NMT-opencode.ru-paraphrase-NMT-Leipzig
Dataset Card for cointegrated/ru-paraphrase-NMT-Leipzig
Dataset Summary
The dataset contains 1 million Russian sentences and their automatically generated paraphrases.
It was created by David Dale (@cointegrated) by translating the rus-ru_web-public_2019_1M corpus from the Leipzig collection into English and back into Russian. A fraction of the resulting paraphrases are invalid, and should be filtered out.
The blogpost "Перефразирование русских текстов: корпуса, модели… See the full description on the dataset page: https://huggingface.co/datasets/cointegrated/ru-paraphrase-NMT-Leipzig.NMT-Crossthinking
Nemotron-CrossThink: Scaling Self-Learning beyond Math Reasoning
Author: Syeda Nahida Akter, Shrimai Prabhumoye, Matvei Novikov, Seungju Han, Ying Lin, Evelina Bakhturina, Eric Nyberg, Yejin Choi,
Mostofa Patwary, Mohammad Shoeybi, Bryan Catanzaro
[Paper][Blog]
Dataset Description
Nemotron-CrossThink is a multi-domain reinforcement learning (RL) dataset designed to improve general-purpose
and mathematical reasoning in large language models (LLMs).
The dataset… See the full description on the dataset page: https://huggingface.co/datasets/Compumacy/NMT-Crossthinking.qianyan_nmt
Qianyan Low-Resource NMT Dataset
"千言数据集：低资源语言翻译" ，旨在帮助研究人员和开发者解决低资源语言翻译的问题。该数据集包含了中文和俄文的5万条双语平行语料，以及中文和泰文、中文和越南文各10万条目标端单语语料。
对于泰文和越南文，使用谷歌翻译进行回译，从而生成对应的中文数据。
source=1表示中文到其他语言的翻译，source=0表示其他语言到中文的翻译，以便区分测试集的语言方向。
详见：
https://aistudio.baidu.com/competition/detail/84/0/introduction
ru-paraphrase-NMT-Leipzig-cleaned
Dataset Description
The dataset is obtained by filtering dataset of russian paraphrases by David Dale with automatic metrics.
The data structure is saved.
Have been deleted:
Paraphrases that have cosine LABSE similarity with source sentences < 0.75.
Paraphrases that are more than 2.5 times longer than source sentences. (Most of them are looped errors of back translation)
Paraphrases that are similar in spelling to the original texts (paraphrases that have ChrF++ similarity > 0.6… See the full description on the dataset page: https://huggingface.co/datasets/fyaronskiy/ru-paraphrase-NMT-Leipzig-cleaned.MemGuide
MemGuide
MemGuide is the training dataset for MemAdapter,
a plug-and-play module that converts retrieved memories into structured planning guidance for
Vision-Language Model (VLM) embodied agents.
Dataset Summary
Each record pairs a task instruction and retrieved memories (spatial, episodic, and semantic)
with structured planning guidance produced by a frontier LLM and filtered by behavioral consensus.
The dataset is used to fine-tune the MemAdapter (Qwen3-14B +… See the full description on the dataset page: https://huggingface.co/datasets/NMThuan032k/MemGuide.task177_para-nmt_paraphrasing
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task177_para-nmt_paraphrasing
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks}… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task177_para-nmt_paraphrasing.NMToxificationParallel corpora for toxicity analysis. Toxic prompts were taken from Toxigen datset and "translated" from toxic to not-toxic with Llama-3-70B.