datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
hle_math_exact_match_no_image_int_answer_random128c4-pt-randMore35M-part04-deduplicated-128000-no-digit-split-mask-train-15003771-lines
Dataset Card for "c4-pt-randMore35M-part04-deduplicated-128000-no-digit-split-mask-train-15003771-lines"
More Information needed
total-300-random-jh-epoch4
total-300-random-jh-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.3890625
Action score: 0.440625
Valid samples: 320/320
leafy_spurge
Background
This dataset comprises 1.3 cm resolution aerial images of grasslands in western Montana, USA, captured by a commercial drone. Many scenes contain leafy spurge (Euphorbia esula), introduced to North America, now widespread in rangeland ecosystems, which is highly invasive and damaging to crop production and biodiversity. Technicians surveyed 1000 points in the study area, noting spurge presence or absence, and recorded each point’s position with precision global… See the full description on the dataset page: https://huggingface.co/datasets/mpg-ranch/leafy_spurge.melee-ranked-replays
Melee Ranked Replays
Anonymized Slippi ranked replays (platinum+) from Super Smash Bros. Melee,
sharded by character and rank pair. Built for behavior-cloning and other
replay-driven ML work on Melee — notably MIMIC.
Contents
Raw .slp files grouped into tarballs by (character, rank_pair, source_archive),
organized into per-character folders:
{CHAR}/
{CHAR}_{rank_pair}_a{N}.tar.gz
metadata/
metadata_a{N}.json
Characters (25): BOWSER, CPTFALCON, DK, DOC, FALCO… See the full description on the dataset page: https://huggingface.co/datasets/erickfm/melee-ranked-replays.mmlu-random-AWan-Syn_77x448x832_600krank_llm_data10k_prompts_ranked
Dataset Card for 10k_prompts_ranked
10k_prompts_ranked is a dataset of prompts with quality rankings created by 314 members of the open-source ML community using Argilla, an open-source tool to label data. The prompts in this dataset include both synthetic and human-generated prompts sourced from a variety of heavily used datasets that include prompts.
The dataset contains 10,331 examples and can be used for training and evaluating language models on prompt ranking tasks. The… See the full description on the dataset page: https://huggingface.co/datasets/data-is-better-together/10k_prompts_ranked.mmlu-random-2argument_quality_ranking_30k
Dataset Card for Argument-Quality-Ranking-30k Dataset
Dataset Summary
Argument Quality Ranking
The dataset contains 30,497 crowd-sourced arguments for 71 debatable topics labeled for quality and stance, split into train, validation and test sets.
The dataset was originally published as part of our paper: A Large-scale Dataset for Argument Quality Ranking: Construction and Analysis.
Argument Topic
This subset contains 9,487 of the arguments only with… See the full description on the dataset page: https://huggingface.co/datasets/ibm-research/argument_quality_ranking_30k.mmlu-random-1vsr_random
VSR: Visual Spatial Reasoning
This is the random set of VSR: Visual Spatial Reasoning (TACL 2023) [paper].
Usage
from datasets import load_dataset
data_files = {"train": "train.jsonl", "dev": "dev.jsonl", "test": "test.jsonl"}
dataset = load_dataset("cambridgeltl/vsr_random", data_files=data_files)
Note that the image files still need to be downloaded separately. See data/ for details.
Go to our github repo for more introductions.
Citation
If you find VSR… See the full description on the dataset page: https://huggingface.co/datasets/cambridgeltl/vsr_random.steady-rans-generalization
Steady-RANS cross-family generalization dataset
Data for the paper "Towards generalized flow field prediction: one model across unseen
object families" (under double blind review; this account is anonymous for that reason).
Trained checkpoints and evaluation code are in the companion model repo:
steady-rans-surrogates.
Steady incompressible k-omega SST (OpenFOAM simpleFoam) external flow around 855 distinct
shapes (17 scripted parametric families plus 40 ModelNet object… See the full description on the dataset page: https://huggingface.co/datasets/BlidReview/steady-rans-generalization.BrushDataUN_Historical_PDF_Article_Text_Corpus
python
dataset = load_dataset("ranWang/UN_Historical_PDF_Article_Text_Corpus", split="train")
or
dataset = load_dataset("ranWang/UN_Historical_PDF_Article_Text_Corpus", split="randomTest")
lang_list = ["ar", "en", "es", "fr", "ru", "zh"]
for row in dataset:
# 获取pdf文章内容
for lang in lang_list:
# type == str
lang_match_file_content = row[lang]
# 如果按页分割
lang_match_file_pages_content = lang_match_file_content.split("\n----\n")
imagenet-1k-rand_blur
Dataset Card for "imagenet-1k-rand_blur"
More Information needed
newyorker_caption_ranking
New Yorker Caption Ranking Dataset
Dataset Descriptions
Homepage: https://nextml.github.io/caption-contest-data/
Repository: https://github.com/yguooo/cartoon-caption-generation
Paper: Humor in AI: Massive Scale Crowd-Sourced Preferences and Benchmarks for Cartoon Captioning
Point of Contact: yguo@cs.wisc.edu
Dataset Summary
We present a novel multimodal preference dataset for creative tasks, consisting of over 250 million human ratings on more than 2.2… See the full description on the dataset page: https://huggingface.co/datasets/yguooo/newyorker_caption_ranking.password_strength_datasetai2thor-random-views-20kvertebrate-v1-issue473-fullwindow-cds-random-val
marin-dna/vertebrate-v1-issue473-fullwindow-cds-random-val
CDS full-window vertebrate projection sequences for the issue #473 random
validation control. The source is the immutable issue #417 accepted-sequence
table.
The split uniformly samples 16,384 original-orientation CDS rows
without replacement using seed 42. Sampling occurs before
reverse-complement augmentation. Selected rows are removed from training;
reverse complements are then added only to the remaining training… See the full description on the dataset page: https://huggingface.co/datasets/marin-dna/vertebrate-v1-issue473-fullwindow-cds-random-val.wikipedia-ja-20230101
range3/wikipedia-ja-20230101
This dataset consists of a parquet file from the wikipedia dataset with only Japanese data extracted. It is generated by the following python code.
このデータセットは、wikipediaデータセットの日本語データのみを抽出したparquetファイルで構成されます。以下のpythonコードによって生成しています。
import datasets
dss = datasets.load_dataset(
"wikipedia",
language="ja",
date="20230101",
beam_runner="DirectRunner",
)
for split,ds in dss.items():
ds.to_parquet(f"wikipedia-ja-20230101/{split}.parquet")
essay-vocab-range-qwen3.5-4b-trl-completions
TRL Completion logs
This dataset contains the completions generated during training using trl.
Find the trained model at https://huggingface.co/bihungba1101/essay-vocab-range-qwen3.5-4b-grpo.
The completions are stored in parquet files, and each file contains the completions for a single step of training (depending on the logging_steps argument).
Each file contains the following columns:
step: the step of training
prompt: the prompt used to generate the completion
completion: the… See the full description on the dataset page: https://huggingface.co/datasets/bihungba1101/essay-vocab-range-qwen3.5-4b-trl-completions.mmlu-random-DTaskMeAnything-v1-imageqa-random
Dataset Card for TaskMeAnything-v1-imageqa-random
TaskMeAnything-v1-imageqa-random dataset
🌐 Website | 📑 Paper | 🤗 Huggingface | 💻 Interface
If you like our project, please give us a star ⭐ on GitHub for latest update.
TaskMeAnything-v1-Random
TaskMeAnything-v1-imageqa-random is a dataset which using
randomly sampled questions from TaskMeAnything-v1, including 5,700 ImageQA questions. The dataset contains 19 splits, while each splits contains 300… See the full description on the dataset page: https://huggingface.co/datasets/weikaih/TaskMeAnything-v1-imageqa-random.steve1-training-data
STEVE-1 Training Data With MineCLIP Embeddings
This dataset contains the MineCLIP-embedded training data used for the MultiSTEVE-1s model zoo. It supports reproducing STEVE-1-style fine-tuning without regenerating MineCLIP embeddings.
Contents
Top-level directories:
dataset_contractor/: OpenAI Contractor Dataset episodes converted for STEVE-1 training.
dataset_mixed_agents/: VPT-generated Minecraft trajectories collected for STEVE-1-style training.
Each episode… See the full description on the dataset page: https://huggingface.co/datasets/randomhuggingfaceuser1273823147/steve1-training-data.trdg_random_en_zh_text_recognition
Dataset Card for "trdg_random_en_zh_text_recognition"
This synthetic dataset was generated using the TextRecognitionDataGenerator(TRDG) open source repo:
https://github.com/Belval/TextRecognitionDataGenerator
It contains images of text with random characters from Engilsh(en) and Chinese(zh) languages.
Reference to the documentation provided by the TRDG repo:
https://textrecognitiondatagenerator.readthedocs.io/en/latest/index.html
TaskMeAnything-v1-videoqa-random
Dataset Card for TaskMeAnything-v1-videoqa-random
TaskMeAnything-v1-videoqa-random dataset
🌐 Website | 📑 Paper | 🤗 Huggingface | 💻 Interface
If you like our project, please give us a star ⭐ on GitHub for latest update.
TaskMeAnything-v1-Random
TaskMeAnything-v1-videoqa-random is a dataset which randomly sampled questions from TaskMeAnything-v1, including 2,700 VideoQA questions. The dataset contains 9 splits, while each splits contains 300 questions… See the full description on the dataset page: https://huggingface.co/datasets/weikaih/TaskMeAnything-v1-videoqa-random.ust-rankings
UST Rankings
Daily course and instructor rating marts for UST Rankings, built from the
ust-archive datasets.
File
Contents
courses.parquet
Current Course metadata by Course Code.
course-ratings.parquet
Longitudinal course ratings by term and criterion.
instructor-ratings.parquet
Longitudinal instructor ratings by term and criterion.
course-rankings.parquet
Latest-term course ratings.
instructor-rankings.parquet
Latest-term instructor ratings.… See the full description on the dataset page: https://huggingface.co/datasets/ust-archive/ust-rankings.RoboTwin_adjust_bottle_randomizedThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "aloha",
"total_episodes": 500,
"total_frames": 68537,
"total_tasks": 424,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 15,
"splits": {
"train": "0:500"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/suz22/RoboTwin_adjust_bottle_randomized.