datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
RoMo-SMPL
RoMo-SMPL — In-the-Wild SMPL Body Motion (RoMo Paper Core)
RoMo-SMPL is the paper-aligned release of the RoMo body motion corpus in SMPL body parameter space (global orientation, 21-joint body pose, shape, translation). Each clip includes five text captions and a three-level semantic taxonomy (category, subcategory, atomic action), with fixed train / val / test splits.
Paper: RoMo: A Large-Scale, Richly Organized Dataset and Semantic Taxonomy for Human Motion Generation… See the full description on the dataset page: https://huggingface.co/datasets/RoMoDataset/RoMo-SMPL.ROMA_proactive
ROMA Proactive Streaming Dataset
Figure: Overview of ROMA's Streaming Dataset. This repository contains the Proactive subset (Green and Purple sections).
Dataset Summary
This repository contains the Proactive Interaction subset of the dataset introduced in the paper ROMA: Real-time Omni-Multimodal Assistant with Interactive Streaming Understanding.
This dataset is designed to train multimodal models for streaming video understanding, specifically focusing on tasks… See the full description on the dataset page: https://huggingface.co/datasets/EurekaTian/ROMA_proactive.rombodawg-Everything_Instruct
Everything-Instruct: Supervised Finetuning Dataset
This dataset contains over 7 000 000 instruction-response pairs for supervised fine-tuning large language models.
It combines the following datasets:
rombodawg/Everything_Instruct
rombodawg/Everything_Instruct_Multilingual
It can be used for:
Improving code generation and debugging
Enhancing creative writing
Improving general instruction followingFor English and many other languages
Processing
Removing duplicate… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/rombodawg-Everything_Instruct.RoMo-HML-263
RoMo-HML-263 — RoMo Body Motion in HumanML3D-263 Features
RoMo-HML-263 is the RoMo body corpus packed in the 263-dimensional HumanML3D motion-feature representation, paired with rich multi-level text descriptions. It is the drop-in companion for training and evaluating models built around the HumanML3D feature set, sized at the RoMo scale (~815K clips).
⚠️ Access: This dataset is currently private / internal. It will be released publicly in conjunction with the RoMo paper.… See the full description on the dataset page: https://huggingface.co/datasets/RoMoDataset/RoMo-HML-263.gemini-3.1-pro-hard-high-reasoning
Dataset Card for Gemini-3.1-Pro-Ultra-Reasoning-5.6M
Dataset Details
Dataset Description
This dataset represents the frontier of synthetic reasoning data, generated by Gemini 3.1 Pro (High Reasoning variant). While smaller in total token volume than its predecessors (5.6M tokens), this corpus prioritizes logical density and multi-step verification.
The move to the 3.1 architecture provides a measurable leap in "System 2" thinking. Unlike standard models… See the full description on the dataset page: https://huggingface.co/datasets/Roman1111111/gemini-3.1-pro-hard-high-reasoning.opus-gpt-swe-frontier-core
SWE Base
Repository-level software engineering trajectories for training coding agents.
2,459 chat trajectories · 48,499 API calls · $837.57 recorded generation cost
SWE-bench · debugging · patching · tools · agents
Overview
SWE Base is a software-engineering dataset centered on real repository issues. Each training example gives an agent a problem statement and captures the multi-turn process of inspecting a codebase, reasoning about a bug… See the full description on the dataset page: https://huggingface.co/datasets/Roman1111111/opus-gpt-swe-frontier-core.RoMo-272
RoMo-272 — RoMo Body Motion in the 272-D Motion Representation
RoMo-272 is the RoMo body-motion corpus (paper core) packed in the 272-dimensional motion representation of Li-xingXiao/272-dim-Motion-Representation — a HumanML3D-derived encoding that augments the standard 263-D HumanML3D layout with 9 additional absolute/global features used by several recent text-to-motion methods. Each clip carries five text captions and a three-level semantic taxonomy, with fixed train / val /… See the full description on the dataset page: https://huggingface.co/datasets/RoMoDataset/RoMo-272.RoMo-SOMA-77
RoMo-SOMA-77 — RoMo Body+Hand Motion in 933-D Kimodo SOMA-77 Features
RoMo-SOMA-77 is the RoMo body+hand corpus packed in a 933-dimensional Kimodo SOMA-77 motion-feature representation, paired with rich multi-level text descriptions. It is the publication target for the SOMA-based body-and-hand model family.
Scope: paper-core (romo_official = True), matching RoMo-SMPL, RoMo-HML-263, and RoMo-272. A small number of clips are dropped where SOMA conversion produced non-finite… See the full description on the dataset page: https://huggingface.co/datasets/RoMoDataset/RoMo-SOMA-77.ROMB-1.0
♦ ROMB
Русское описание и инструкция
ROMB (Russian Olympiad Math Benchmark) evaluates models on Russian-language
school olympiad mathematics. The test set contains 2552 text-only tasks:
1716 arithmetic/other tasks, 644 logic tasks, and 192 geometry tasks. Tasks have
typed answers, answer-format notes, and per-task checking rules.
The evaluator also supports configurable v3 runs: native thinking, optional
JSON Schema constrained decoding, plain or \boxed{…} answers, and… See the full description on the dataset page: https://huggingface.co/datasets/d0rj/ROMB-1.0.aosp-rom-dataset
Modern OnePlus & Xiaomi Flagship AOSP Engineering Dataset
Structured, lightweight multi-domain shards covering:
device_trees_kernel: OnePlus (SM8550/SM8450), Xiaomi (SM8550/SM8450), GKI modules, BoardConfig, and DTS bindings.
systemui_launcher: Lawnchair spring physics, AGSL runtime shaders, and Avium/Axion/PixelOS UI panels.
build_sepolicy: Soong blueprints (Android.bp), product makefiles, and strict SELinux rules (.te).
frameworks: Native SurfaceFlinger C++ compositor and… See the full description on the dataset page: https://huggingface.co/datasets/ajaysinghsat/aosp-rom-dataset.WikiSpell_custom
WikiSpell
Description
This dataset is a custom implementation of the WikiSpell dataset introduced in Character-Aware Models Improve Visual Text Rendering by Liu et al. (2022).
Similarly to the original WikiSpell dataset, the training set is composed of 5000 words taken uniformly from the 50% least common Wiktionary words (taken from this Wiktionary extraction), and 5000 words sampled according to their frequencies taken from the 50% most common Wiktionary words.
The… See the full description on the dataset page: https://huggingface.co/datasets/RomanCast/WikiSpell_custom.gemini-3-pro-10000x-hard-high-reasoning
Dataset Card for Gemini-3-Pro-Reasoning-10000x-high-reasoning
Dataset Details
Dataset Description
Suggestion: I would use it to fine tune glm- 4.7-flash, or other 30b moe models, but 2-20b llms work perfectly, you can fine tune Nanbeige 4.1 - 3b, gpt-oss:20b, or qwen3: 4b, 8b(note: better to fine tune newest versions(2507 4b qwen3 , or qwen 3 vl:8b)) for maximum improvement.
This dataset is a high-complexity synthetic reasoning corpus containing… See the full description on the dataset page: https://huggingface.co/datasets/Roman1111111/gemini-3-pro-10000x-hard-high-reasoning.reddit_dataset_51
Bittensor Subnet 13 Reddit Dataset
Miner Data Compliance Agreement
In uploading this dataset, I am agreeing to the Macrocosmos Miner Data Compliance Policy.
Dataset Summary
This dataset is part of the Bittensor Subnet 13 decentralized network, containing preprocessed Reddit data. The data is continuously updated by network miners, providing a real-time stream of Reddit content for various analytical and machine learning tasks.
For more… See the full description on the dataset page: https://huggingface.co/datasets/romban38/reddit_dataset_51.Romulus-cpt-fr
Romulus, continually pre-trained models for French law.
Romulus is a series of continually pre-trained models enriched in French law and intended to serve as the basis for a fine-tuning process on labeled data. Please note that these models have not been aligned for the production of usable text as they stand, and will certainly need to be fine-tuned for the desired tasks in order to produce satisfactory results.
The training corpus is made up of around 34,864,949 tokens… See the full description on the dataset page: https://huggingface.co/datasets/louisbrulenaudet/Romulus-cpt-fr.x_dataset_51
Bittensor Subnet 13 X (Twitter) Dataset
Miner Data Compliance Agreement
In uploading this dataset, I am agreeing to the Macrocosmos Miner Data Compliance Policy.
Dataset Summary
This dataset is part of the Bittensor Subnet 13 decentralized network, containing preprocessed data from X (formerly Twitter). The data is continuously updated by network miners, providing a real-time stream of tweets for various analytical and machine learning… See the full description on the dataset page: https://huggingface.co/datasets/romban38/x_dataset_51.roman-urdu-qwen25-3b-blindspot
Roman Urdu / code-switch blind spot (Qwen2.5-3B-Instruct)
Hand-built eval: 8 Pakistani situations x 3 surfaces (English, formal Urdu, Roman Urdu).
Model: Qwen/Qwen2.5-3B-Instruct. Greedy decoding, 4-bit, Colab T4.
Evaluation
condition
pass
n
rate
english
7
8
0.88
formal_urdu
3
8
0.38
roman_urdu
1
8
0.12
Files: prompts.jsonl, outputs.jsonl, judged.jsonl, scores.json
Roman Urdu traces:
01_ro: NADRA described as a motor-vehicle department
02_ro:… See the full description on the dataset page: https://huggingface.co/datasets/Ashar086/roman-urdu-qwen25-3b-blindspot.roman-urdu-alpaca-qa-mix
Dataset Card for Roman Urdu + Alpaca QA Mix
This dataset is intended to support fine-tuning and evaluation of language models that understand and respond to Roman Urdu and English instructions. It consists of 1,022 records in total:
500 examples in Roman Urdu generated from high-quality Urdu sources and transliterated using the ChatGPT API.
500 examples in English randomly sampled from the Stanford Alpaca dataset.
The dataset follows the same format as Alpaca-style instruction… See the full description on the dataset page: https://huggingface.co/datasets/Redgerd/roman-urdu-alpaca-qa-mix.japanese-triplet-lifestyle-romance
🏯 Japanese Preference Dataset: Counseling & Advice (Free Sample)
This repository provides a free sample of a Japanese preference learning dataset designed for Direct Preference Optimization (DPO), RLHF, Reward Modeling, response ranking, and Japanese LLM alignment.
The dataset focuses on realistic Japanese counseling and advice scenarios, helping language models learn not only factual correctness but also empathy, contextual understanding, and practical response quality.… See the full description on the dataset page: https://huggingface.co/datasets/wasabiP/japanese-triplet-lifestyle-romance.FairytaleQA-translated-romanian
Dataset Card for FairytaleQA-translated-ptBR
Dataset Summary
This repository contains the Romanian machine-translated version of the original English FairytaleQA dataset (https://huggingface.co/datasets/WorkInTheDark/FairytaleQA). FairytaleQA is an open-source dataset designed to enhance comprehension of narratives, aimed at students from kindergarten to eighth grade. The dataset is meticulously annotated by education experts following an evidence-based theoretical… See the full description on the dataset page: https://huggingface.co/datasets/benjleite/FairytaleQA-translated-romanian.thai-romanization-datasetDataset from github.com/wannaphong/thai-romanization/blob/master/dataset/data.csv
Wikitext
I made this by downloading and extracting the wikidump (smaller version)
This might be better for fine tuning
its a jsonl file
if you're low on space, ill be giving the zipped jsonl too :D
385,692 lines
or around 385,000
Devnagari-Romanized-Pair
Dataset Overview
The dataset devanagari romanized pair contains, 959 rows, where each row has one English sentence and its corresponding Nepali translations both in the devanagari script and in romanized format, the size of the data set is less than 1,000 elements and it's designed for use in Translation, text generation and text to text generation tasks.
English-Romanian-Magpie-Reasoning
English-Romanian Translation Pairs from Magpie-Reasoning
This dataset contains 150,000 high-quality English-Romanian parallel translation pairs derived from the Magpie-Reasoning dataset, specifically designed for training and evaluating machine translation models with a focus on technical, mathematical, and code-related content.
Source Datasets
This dataset is created by aligning:
English: Magpie-Align/Magpie-Reasoning-V1-150K
Romanian: OpenLLM-Ro/ro_sft_magpie_reasoning… See the full description on the dataset page: https://huggingface.co/datasets/Yxanul/English-Romanian-Magpie-Reasoning.romani_compasito
Romani Prompts (Kompasito)
Prompt/context pairs derived from Kompasito — Manual on Human Rights Education for Children (Council of Europe), translated into Romani. Built for adapting LLMs to Romani via SFT/DPO.
Structure
Each row is a JSON object:
prompt — an English instruction sampled from one of three buckets: comprehension, translation, or generative.
context — a Romani text chunk (~1000 chars, 150-char overlap) from the source PDF.
Each surviving chunk appears in 3… See the full description on the dataset page: https://huggingface.co/datasets/Ilia-Iliev/romani_compasito.romath
RoMath - A Mathematical Reasoning Benchmarking Suite from Descriptions in 🇷🇴 Romanian 🇷🇴"
This is the official dataset for RoMath. It currently is comprised of the test and training splits for RoMath-Baccalaureate, RoMath-Competitions and RoMath-Synthetic.
Mathematics has long been conveyed through natural language, primarily for human understanding. With the rise of mechanized mathematics and proof assistants, there is a growing need to understand informal mathematical text… See the full description on the dataset page: https://huggingface.co/datasets/cosmadrian/romath.FEDERICO-GARCIA-LORCA-canciones-poemas-romances-annotated
Federico García Lorca - Annotated Poetry Dataset
A curated and annotated dataset of 283 poems by Federico García Lorca, spanning 9 of his major works (1921--1940). Each poem is enriched with publication metadata and GPT-4-generated thematic and contextual annotations.
Use Case: LLM Generalization Evaluation
This dataset was created to evaluate how well large language models can generalize literary style from a small, domain-specific corpus. It has been used to fine-tune… See the full description on the dataset page: https://huggingface.co/datasets/xaviviro/FEDERICO-GARCIA-LORCA-canciones-poemas-romances-annotated.padel-indonesia-dataset
🏸 Padel Indonesia Dataset
Dataset instruksi Q&A komprehensif tentang olahraga Padel di Indonesia
Oleh Jekardah AI Labs — Romi Nur Ismanto
Overview
Dataset ini berisi 1,291 pasangan instruksi-output dalam Bahasa Indonesia yang mencakup seluruh aspek olahraga Padel di Indonesia. Dirancang untuk fine-tuning LLM agar bisa menjawab pertanyaan seputar Padel dengan akurat dan komprehensif.
Format
Setiap entry mengikuti format Alpaca-style:
{
"instruction":… See the full description on the dataset page: https://huggingface.co/datasets/romizone/padel-indonesia-dataset.romeo_and_juliet
Dataset Card for romeo_and_juliet
This dataset has been created with distilabel.
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:
distilabel pipeline run --config "https://huggingface.co/datasets/ZenithVortex/romeo_and_juliet/raw/main/pipeline.yaml"
or explore the configuration:
distilabel pipeline info --config… See the full description on the dataset page: https://huggingface.co/datasets/ZenithVortex/romeo_and_juliet.steve-jobs-question-and-answersmy-distiset-3276ad2f
Dataset Card for my-distiset-3276ad2f
This dataset has been created with distilabel.
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:
distilabel pipeline run --config "https://huggingface.co/datasets/RomeKim/my-distiset-3276ad2f/raw/main/pipeline.yaml"
or explore the configuration:
distilabel pipeline info --config… See the full description on the dataset page: https://huggingface.co/datasets/RomeKim/my-distiset-3276ad2f.