datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
10k_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.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.random-small-github-repositories
random-small-github-repositories
A collection of 5,613 small-to-medium open-source GitHub repositories, packaged as zipped archives alongside a metadata CSV. Intended as a seed dataset for code retrieval, context engineering, and SWE-bench-style dataset construction tasks.
Contents
seed_small_repos.csv — metadata for each repo (owner, repo_name, stars, license, repo_hash)
repos-zipped/ — one .zip per repo, named {repo_hash}.zip
unzipper.py - unzipping python… See the full description on the dataset page: https://huggingface.co/datasets/AmanPriyanshu/random-small-github-repositories.random-python-github-repositories
random-python-github-repositories
A collection of 1650 open-source Python GitHub repositories, packaged as zipped archives alongside a metadata CSV. Intended as a seed dataset for code retrieval, context engineering, and SWE-bench-style dataset construction tasks. All repos contain 250+ .py files.
Contents
repos_meta_data.csv — metadata for each repo (owner, repo_name, stars, license, py_file_count, alpha_hash)
repos-zipped/ — one .zip per repo, named… See the full description on the dataset page: https://huggingface.co/datasets/AmanPriyanshu/random-python-github-repositories.cancer-knowledge-base
Cancer Knowledge Base — the open, verified oncology KB for RAG & LLM evaluation
The only open CC-BY-4.0 oncology knowledge base that combines:
110/110 trials cited with PMID + NCT + PubMed/ClinicalTrials.gov URLs, and 32 prognosis
rows linked to verified SEER 2016–2022 references — no LLM-synthetic dataset has this.
A provable 152-question MCQ benchmark — every answer derives from this KB's own structured
data and carries a citation + golden docs, so it is open-book verifiable… See the full description on the dataset page: https://huggingface.co/datasets/ranjithraj/cancer-knowledge-base.low-quality-random-sft-data-I-had-laying-around
low-quality-random-sft-data-I-had-laying-around
Exactly what it says on the tin. Random synthetic ChatML SFT scraps I had laying around on disk. Not curated. Not high quality. Possibly cursed. Useful if you want cheap filler / toy SFT data.
Configs
Config
Rows
What it is
counting
15,000
Letter counts, palindromes, tiny string puzzles
word-problems
19,587
Synthetic arithmetic word problems
math
213,693
Synthetic math Q&A ChatML (merged from several… See the full description on the dataset page: https://huggingface.co/datasets/hudsongouge/low-quality-random-sft-data-I-had-laying-around.Mr-GSM8KView the project page:
https://github.com/dvlab-research/DiagGSM8K
see our paper at https://arxiv.org/abs/2312.17080
Description
In this work, we introduce a novel evaluation paradigm for Large Language Models,
one that challenges them to engage in meta-reasoning. Our paradigm shifts the focus from result-oriented assessments,
which often overlook the reasoning process, to a more holistic evaluation that effectively differentiates
the cognitive capabilities among models. For… See the full description on the dataset page: https://huggingface.co/datasets/Randolphzeng/Mr-GSM8K.Amazon-combined
Amazon Combined Dataset
E-commerce dataset that combines metadata, reviews, and sample question/answer pairs. combined.json contains the dataset and user2asin.json contains a file that maps user_id from reviews to an ASIN for capturing user preferences.
Data Fields
Field
Type
Explanation
main_category
str
Main category (i.e., domain) of the product.
title
str
Name of the product.
average_rating
float
Rating of the product shown on the product page.… See the full description on the dataset page: https://huggingface.co/datasets/randomath/Amazon-combined.agent-trajectories-swesmith-random-subset
Agent Trajectories: SWE-Smith Random Subset — Single Model
Summary
Full multi-turn agent trajectories collected from a random subset of SWE-Smith issues,
generated with a single model per trajectory (no branching or lookahead).
Contains a resolved column from SWE-bench evaluation.
Intended for SFT of agent models on diverse, synthetically generated coding tasks.
Data Collection
Each trajectory was produced by a mini-swe-agent run with an LLM router selecting… See the full description on the dataset page: https://huggingface.co/datasets/JetBrains-Research/agent-trajectories-swesmith-random-subset.MutQA
CrossValQA
CrossValQA is a cross-validated, sentence-grounded question-answering
dataset about genetic mutations, constructed from full-text PubMed articles.
Every record links a natural-language question to a specific variant, a
specific PubMed article, and a specific cited sentence span, and every
answer was produced by two independent LLMs that had to agree before the
record was admitted.
The released train/test splits (homology and random configs)
contain only cross-grounded… See the full description on the dataset page: https://huggingface.co/datasets/random987654321/MutQA.sinhala-corpus-b-random-1m
Randomly Curated Sinhala Corpus
A randomly sampled subset of 1M Sinhala sentences from the Minuri/diverse_sinhala_dataset corpus, used for continual pretraining of LLaMA 3.2 1B (Model B) as part of a diversity-driven Sinhala language model adaptation study.
Corpus variants in this series:
Minuri/sinhala-corpus-a-news-1m - News-only subset (domain-homogeneous baseline)
Minuri/sinhala-corpus-b-random-1m - Random subset (random baseline) - this repo
Minuri/sinhala-corpus-c-diverse-1m… See the full description on the dataset page: https://huggingface.co/datasets/Minuri/sinhala-corpus-b-random-1m.wdb-islamic-finance-benchmark
WDB Benchmark: Western Default Bias in Islamic Finance
Dataset Description
This benchmark tests whether Large Language Models exhibit Western Default Bias (WDB) - the tendency to provide Western/conventional finance answers even when the context implies Islamic finance should be used.
The Problem
When a user in Saudi Arabia or UAE asks a financial question, they likely expect Shariah-compliant advice. However, LLMs trained predominantly on Western data may… See the full description on the dataset page: https://huggingface.co/datasets/Raniahossam33/wdb-islamic-finance-benchmark.Sinhala-News-Wiki-text-corpus
Sinhala-News-Wiki-Text-Corpus
Containing news articles from various Sinhala news sites along with Sinhala Wikipedia pages.
Dataset Overview
Language: Sinhala (සිංහල)
Content: Sinhala news articles from various sites
Data format: Parquet
Number of Records: 18,201 rows (as per current size)
Dataset Structure
Each record consists of the following fields:
category: The news category (e.g., "Other-news, Local-news, wiki, International-news").
site: The site's… See the full description on the dataset page: https://huggingface.co/datasets/janani-rane/Sinhala-News-Wiki-text-corpus.