datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
leetcode-problem-solutions
LeetCode Solution Dataset
This dataset contains community-contributed LeetCode solutions scraped from public discussions and solution pages, enriched with metadata such as vote counts, author info, tags, and full code content. The goal is to make high-quality, peer-reviewed coding solutions programmatically accessible for research, analysis, educational use, or developer tooling.
Column Descriptions
Column Name
Type
Description
question_slug
string
The unique… See the full description on the dataset page: https://huggingface.co/datasets/kaysss/leetcode-problem-solutions.codeforces-problems-7kleetcode-problem-detailed
LeetCode Scraper Dataset
This dataset contains information scraped from LeetCode, including problem details, metadata, and related files. It is designed to assist developers in analyzing LeetCode problems, generating insights, and building tools for competitive programming or educational purposes.
questions_deets.csv
Contains detailed information about each problem, including problem descriptions, constraints, and examples.
Columns:
questionFrontendId: Unique problem ID.… See the full description on the dataset page: https://huggingface.co/datasets/kaysss/leetcode-problem-detailed.olympiad_style_integer_math_problems
Olympiad Math Corpus
Version: v2.1.1
Release date: 2026-05-03
59,486 synthetically generated olympiad-style math problems with verified integer answers and formal computation graphs.
Loading
from datasets import load_dataset
ds = load_dataset("mihailgribov/olympiad_style_integer_math_problems", split="train")
lemma_applicability is stored as list[{lemma, status}] rather than a sparse dict (required for Arrow-based consumers). To convert to a dict for local use:… See the full description on the dataset page: https://huggingface.co/datasets/mihailgribov/olympiad_style_integer_math_problems.ParallelKernelBench_Problems
ParallelKernelBench (benchmark)
Reference problems for ParallelKernelBench: a benchmark for LLM-generated multi-GPU CUDA kernels.
This dataset contains 87 reference implementations in reference/ and the input tensor specification in utils/input_output_tensors.py. Inputs are deterministic — reproduce them with create_input_tensor(rank, world_size, problem_id, base_shape, dtype, trial) from that file; you do not need stored .pt files.
Files
Path
Description… See the full description on the dataset page: https://huggingface.co/datasets/togethercomputer/ParallelKernelBench_Problems.ParallelKernelBench_Problems
ParallelKernelBench (benchmark)
Reference problems for ParallelKernelBench: a benchmark for LLM-generated multi-GPU CUDA kernels.
This dataset contains 87 reference implementations in reference/ and the input tensor specification in utils/input_output_tensors.py.
Files
Path
Description
data/problems.parquet
One row per problem (tabular access)
reference/*.py
Reference solution() implementations
utils/input_output_tensors.py
Input/output tensor… See the full description on the dataset page: https://huggingface.co/datasets/willychan21/ParallelKernelBench_Problems.finecf-problems
Dataset Card for FineCF Problems
Dataset description
FineCF Problems is a dataset of 9,768 Codeforces problems, each paired with a cleaned, per-problem editorial explaining the solution approach. Problems span the full difficulty range (800 to 3500) and cover a wide variety of algorithmic topics including dp, graphs, math, greedy, data structures, and more.
You can load the dataset as follows:
from datasets import load_dataset
ds =… See the full description on the dataset page: https://huggingface.co/datasets/touristgpt/finecf-problems.DSA-Coding-Problems-and-Solutions-Dataset
Dataset Description
This dataset is a large-scale collection of Data Structures and Algorithms (DSA) code, containing 12,385 code files with 3.86 million lines of code and 25.01 million lexical tokens, designed to support the development of advanced code generation models, programming assistants, software engineering AI systems, and code intelligence applications.
It consists of real-world DSA implementations covering a wide range of algorithms, data structures, problem-solving… See the full description on the dataset page: https://huggingface.co/datasets/InfoBayAI/DSA-Coding-Problems-and-Solutions-Dataset.open-problem-atlas
OpenProblemAtlas: Open Problems Dataset
A structured, machine-readable dataset of unsolved problems in mathematics,
theoretical computer science, and mathematical physics.
Why This Dataset?
Existing math benchmarks (MATH, GSM8K, MiniF2F) contain solved problems.
This dataset contains unsolved problems -- the frontier of human knowledge.
Use it to:
Benchmark AI theorem proving systems on problems with unknown answers
Train models to understand the structure of open… See the full description on the dataset page: https://huggingface.co/datasets/Tommysha/open-problem-atlas.