datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
requests
Open LLM Leaderboard Requests
This repository contains the request files of models that have been submitted to the Open LLM Leaderboard.
You can take a look at the current status of your model by finding its request file in this dataset. If your model failed, feel free to open an issue on the Open LLM Leaderboard! (We don't follow issues in this repository as often)
Evaluation Methodology
The evaluation process involves running your models against several benchmarks from… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/requests.leaderboard-requestsswallow-math-v2
SwallowMath-v2
Resources
📑 arXiv: Read our paper for detailed methodology at arXiv:2505.02881.
🤗 Sister Dataset: Discover SwallowCode2, our companion dataset for code generation.
🧮 What is it?
SwallowMath-v2 is a large-scale mathematical dataset containing 32 billion tokens, developed as the successor to SwallowMath-v1.
Building on the success of v1, this release aims to construct a larger-scale and more permissively licensed corpus to support open and… See the full description on the dataset page: https://huggingface.co/datasets/tokyotech-llm/swallow-math-v2.tm-system_promptdrh-System-Prompt-processedturkish-llm-dataset
Turkish Pretraining Corpus
Dataset Description
This dataset is a Turkish pretraining corpus created by combining BellaTurca (excluding ForumSohbetleri), Cosmos-Turkish-Corpus-v1.0, and FineWeb-2 Turkish Categorized, followed by cleaning, normalization, and deduplication. It is intended for the development, training, and evaluation of Turkish language models.
This dataset was prepared as part of a capstone project conducted by a group of students from Sabancı… See the full description on the dataset page: https://huggingface.co/datasets/tascib/turkish-llm-dataset.swallow-code-v2
SwallowCode-v2
Resources
📑 arXiv: Read our paper for detailed methodology and results at arXiv:2505.02881.
🤗 Sister Dataset: Discover SwallowMath-v2, our companion dataset for mathematical reasoning.
💻 What is it?
SwallowCode-v1 was a high-quality Python code dataset generated through an LLM-based rewriting pipeline.
However, it had two significant limitations:
(1) it was distributed under the Llama 3.3 Community License, and
(2) its size was limited to… See the full description on the dataset page: https://huggingface.co/datasets/tokyotech-llm/swallow-code-v2.opc-annealing-corpus
OpenCoder Dataset
The OpenCoder dataset is composed of the following datasets:
opc-sft-stage1: the sft data used for opencoder sft-stage1
opc-sft-stage2: the sft data used for opencoder sft-stage2
opc-annealing-corpus: the synthetic data & algorithmic corpus used for opencoder annealing <-- you are here
fineweb-code-corpus: the code-related page recalled from fineweb
fineweb-math-corpus: the math-related page recalled from finewebrefineCode-code-corpus-meta: the meta-data of… See the full description on the dataset page: https://huggingface.co/datasets/OpenCoder-LLM/opc-annealing-corpus.perl-20250811raku-20250811guidelines
🎉 NEW DROP 🎉 PubMed Guidelines
We just added 1627 clinical guidelines found in PubMed and PubMed Central to the dataset on December 23rd, 2023. Merry Christmas!
Clinical Guidelines
The Clinical Guidelines corpus is a new dataset of 47K clinical practice guidelines from 17 high-quality online medical sources. This dataset serves as a crucial component of the original training corpus of the Meditron Large Language Model (LLM). We publicly release a subset of 37K articles… See the full description on the dataset page: https://huggingface.co/datasets/epfl-llm/guidelines.rank_llm_datallmail-inject-challenge
Dataset Summary
This dataset contains a large number of attack prompts collected as part of the now closed LLMail-Inject: Adaptive Prompt Injection Challenge.
We first describe the details of the challenge, and then we provide a documentation of the dataset
For the accompanying code, check out: https://github.com/microsoft/llmail-inject-challenge.
Citation
@article{abdelnabi2025,
title = {LLMail-Inject: A Dataset from a Realistic Adaptive Prompt Injection… See the full description on the dataset page: https://huggingface.co/datasets/microsoft/llmail-inject-challenge.dart-20250811alpaca-gpt4-data-zh
Dataset Card for "alpaca-gpt4-data-zh"
All of the work is done by this team.
Usage and License Notices
The data is intended and licensed for research use only. The dataset is CC BY NC 4.0 (allowing only non-commercial use) and models trained using the dataset should not be used outside of research purposes.
English Dataset
Found here
Citation
@article{peng2023gpt4llm,
title={Instruction Tuning with GPT-4},
author={Baolin Peng, Chunyuan Li… See the full description on the dataset page: https://huggingface.co/datasets/llm-wizard/alpaca-gpt4-data-zh.llm_pt_leaderboard_resultsenron-emailThis dataset includes emails from Enron Email Dataset with prompts processed from Are Large Pre-Trained Language Models Leaking Your Personal Information?.
To use the dataset, you can run the following in LLM-PBE.
from data.enron import EnronDataset
ds = EnronDataset(data_path="data/enron", pseudonymize=False)
MathX-hatoripinocchio-resultsJQL-LLM-Edu-Annotations
📚 JQL Educational Quality Annotations from LLMs
This dataset provides 17,186,606 documents with high-quality LLM annotations for evaluating the educational value of web documents, and serves as a benchmark for training and evaluating multilingual LLM annotators as described in the JQL paper.
📝 Dataset Summary
Multilingual document-level quality annotations scored on a 0–5 educational value scale by three state-of-the-art LLMs:
Gemma-3-27B-it, Mistral-3.1-24B-it… See the full description on the dataset page: https://huggingface.co/datasets/JQL-AI/JQL-LLM-Edu-Annotations.llm-jp-corpus-v4-ja_wiki
llm-jp-corpus-v4 — ja_wiki
Mirror of the ja/ja_wiki sub-corpus of LLM-jp Corpus v4,
built by the LLM-jp Corpus Building WG (NII).
Source: https://gitlab.llm-jp.nii.ac.jp/datasets/llm-jp-corpus-v4
Sub-corpus: ja_wiki
Files: 6 × jsonl.gz (1.9 GB compressed)
Format: one JSON object per line, with a text key and a meta key
(document id, URL, and other provenance fields).
Directory layout mirrors the upstream repository.
License
CC BY-SA 3.0 — inherited from the… See the full description on the dataset page: https://huggingface.co/datasets/Podtech/llm-jp-corpus-v4-ja_wiki.KoHRM-Text-1.4B-prepared-data
KoHRM-Text-1.4B Prepared Data
This dataset repository contains prepared HRM-Text V1Dataset artifacts for KoHRM-Text-1.4B.
The data is intended for continued pretraining and staged training with the project code at:
https://github.com/LLM-OS-Models/KoHRM-text
https://huggingface.co/LLM-OS-Models/KoHRM-Text-1.4B
https://huggingface.co/LLM-OS-Models/HRM-Text-Ko-Terminal-Tokenizer-131K
The upstream architecture and training method are based on:
Paper:… See the full description on the dataset page: https://huggingface.co/datasets/LLM-OS-Models/KoHRM-Text-1.4B-prepared-data.swallow-math
SwallowMath
October 21, 2025: Newer versions are available: SwallowCode-v2 and SwallowMath-v2 have been released with improved rewriting pipelines.
Resources
🐙 GitHub: Explore the project repository, including pipeline code and prompts at rioyokotalab/swallow-code-math.
📑 arXiv: Read our paper for detailed methodology and results at arXiv:2505.02881.
🤗 Sister Dataset: Discover SwallowCode, our companion dataset for code generation.
What is it?… See the full description on the dataset page: https://huggingface.co/datasets/tokyotech-llm/swallow-math.M-IFEval-Jaresultsswallow-code
SwallowCode
Notice
May 21, 2025: We have deleted ablation/exp1-the-stack-v2-train-smol-ids-python because it was flagged as potentially containing unsafe data collected from the Python subset of https://huggingface.co/datasets/bigcode/the-stack-v2-train-smol-ids. However, since this dataset can be reconstructed from the-stack-v2-train-smol-ids, there is no issue in terms of reproducibility.
May 21, 2025: ClamAV has flagged “Win.Trojan.MSShellcode-88” in… See the full description on the dataset page: https://huggingface.co/datasets/tokyotech-llm/swallow-code.fineweb_edu_10B_for_crypto-LLMscaling-data-constrained-llms
Scaling Data-Constrained Language Models with Synthetic Data
This repository provides the pre-training corpora used in Scaling Data-Constrained Language Models with Synthetic Data (Findings of EACL 2026).
Overview
This repository contains multiple corpora designed to study data augmentation strategies for pre-training Japanese LLMs under a data-constrained data setting.
Starting from a limited Japanese Web corpus and a larger English Web corpus, we construct three… See the full description on the dataset page: https://huggingface.co/datasets/llm-jp/scaling-data-constrained-llms.SLT-Task2-Post-ASR-Speaker-Tagging
Dataset Name: Dataset for ASR Speaker-Tagging Corrections (Speaker Diarization)
Description
This dataset is pairs of erroneous ASR output and speaker tagging, which are generated from a ASR system and speaker diarization system.
Each source erroneous transcription is paired with human-annotated transcription, which has correct transcription and speaker tagging.
SEGment-wise Long-form Speech Transcription annotation (SegLST), the file format used in the CHiME challenges… See the full description on the dataset page: https://huggingface.co/datasets/GenSEC-LLM/SLT-Task2-Post-ASR-Speaker-Tagging.NacidCette dataset est le corpus d'entraînement principal du SLM lam (lam-1, lam-2, lam-3, et supérieur.),
il est agrandit régulièrement pour le développement des nouvelles itérations et versions du SLM lam et plus largement, de la série de SLM lamina.
Nous ne cherchons pas à faire de lam, un LLM toute de suite en une traite, mais un SLM progressif
🛑 : Lam, sur toutes ses iterations et modèles (Lam-1, Lam-2, Lam-3 , et supérieur etc...), sont des créations de Clemylia, et du studio LES-IA-ETOILES.… See the full description on the dataset page: https://huggingface.co/datasets/LLM-CLEM/Nacid.