datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
uet_iai_nlp_data_for_llmsData sources come from the following categories:
1.Web crawler dataset:
Website UET (ĐH Công nghệ): tuyensinh.uet.vnu.edu.vn; new.uet.vnu.edu.vn
Website HUS (ĐH KHTN): hus.vnu.edu.vn
Website EUB (ĐH Kinh tế): ueb.vnu.edu.vn
Website IS (ĐH Quốc tế): is.vnu.edu.vn
Website Eduacation (ĐH Giáo dục): education.vnu.edu.vn
Website NXB ĐHQG: press.vnu.edu.vnList domain web crawler
CC100:link to CC100 vi
Vietnews: link to bk vietnews dataset
C4_vi: link to C4_vi
Folder Toxic store files demo… See the full description on the dataset page: https://huggingface.co/datasets/group2sealion/uet_iai_nlp_data_for_llms.llm-srbench
LLM-SRBench: Benchmark for Scientific Equation Discovery with LLMs
We introduce LLM-SRBench, a comprehensive benchmark with 239 challenging problems across four scientific domains specifically designed to evaluate LLM-based scientific equation discovery methods while preventing trivial memorization.
Our benchmark comprises two main categories: LSR-Transform, which transforms common physical models into less common mathematical representations to test reasoning beyond memorization… See the full description on the dataset page: https://huggingface.co/datasets/nnheui/llm-srbench.Videos-Dataset-For-LLMs-RAG-That-Require-Audio-Vidoes-And-Text
Dataset Overview
A collection of 27 domains (“topics”) and 3100 question-answer pair.
Each topic comes with average 117 QA pairs.Every QA entry comes with:
references: one or more source files the answer is extracted from
time with each reference comes the starting and ending time the answer is extracted from the reference
video_files: the video files where the answer can be found
(future) video title & description from metadata.csv
File structure
You-Are-Here!/… See the full description on the dataset page: https://huggingface.co/datasets/elmoghany/Videos-Dataset-For-LLMs-RAG-That-Require-Audio-Vidoes-And-Text.scaling-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.llm_speedrun
LLM Speedrun token streams
Pre-tokenized training artifacts for the LLM speedrun exercises.
File
Description
Tokens
tokenizer_50M.bpe
JSON-serialized BPE tokenizer
—
fineweb-edu-10BT.shuffle.bin
Shuffled FineWeb-Edu sample/10BT token stream
9,440,023,113
smoltalk.shuffle.bin
Shuffled SmolTalk data/all token stream
875,269,408
The .bin files are headerless, little-endian unsigned 16-bit token IDs and can be memory-mapped with NumPy:
from huggingface_hub import… See the full description on the dataset page: https://huggingface.co/datasets/zkolter/llm_speedrun.Multi-turn_Long-context_Benchmark_for_LLMs
LoopServe: An Adaptive Dual-phase LLM Inference Acceleration System for Multi-Turn Dialogues
Arxiv: https://www.arxiv.org/abs/2507.13681
Huggingface: https://huggingface.co/papers/2507.13681
Introduction
LoopServe Multi-Turn Dialogue Benchmark is a comprehensive evaluation dataset comprising multiple diverse datasets designed to assess large language model performance in realistic conversational scenarios.
Unlike traditional benchmarks that place queries only at the end… See the full description on the dataset page: https://huggingface.co/datasets/TreeAILab/Multi-turn_Long-context_Benchmark_for_LLMs.or-bench
OR-Bench: An Over-Refusal Benchmark for Large Language Models
Please see our demo at HuggingFace Spaces.
Overall Plots of Model Performances
Below is the overall model performance. X axis shows the rejection rate on OR-Bench-Hard-1K and Y axis shows the rejection rate on OR-Bench-Toxic. The best aligned model should be on the top left corner of the plot where the model rejects the most number of toxic prompts and least number of safe prompts. We also plot a blue line… See the full description on the dataset page: https://huggingface.co/datasets/bench-llms/or-bench.DEBATE
DEBATE: Diverse Multi-Agent Debates
This dataset is presented in the paper "MALLM: Multi-Agent Large Language Models Framework".
Citation
comming soon.
dec1-jme-student-sourcing-training-and-llmsGlobal-LLMs-Replies
Global LLMs Replies
GPT-4o
-> 74,644 rows
mixtral-8x22b
-> 13,129 rows
claude-3-haiku
-> 3,871 rows
llms-journ-sourcingThis is the initial dataset release for our preprint paper "Measuring Large Language Models Capacity to Annotate Journalistic Sourcing" at https://arxiv.org/abs/2501.00164
We have proposed a benchmark for major foundational LLMs for journalistic sourcing as a scenario.
This dataset has the following folders:
news story samples
ground truth journalistic sourcing annotations for each of the 34 news articles
Prompts used (system prompt -- definitions, and user prompt -- instructions)
The… See the full description on the dataset page: https://huggingface.co/datasets/subbuvincent/llms-journ-sourcing.llmsql-2.0-fine-tune-ready
LLMSQL Benchmark 2.0 (Finetune-Ready)
This benchmark is designed to evaluate text-to-SQL models. For usage of this benchmark see llmsql-bench/llmsql-2.0.
This repository contains a finetune-ready version of the LLMSQL benchmark: LLMSQL 2.0 on Hugging Face.
The dataset is structured in a messages format suitable for instruction-tuned models, where each example has a messages field. This field is a list of dictionaries with:
"role": "user" — the input question or prompt
"role":… See the full description on the dataset page: https://huggingface.co/datasets/llmsql-bench/llmsql-2.0-fine-tune-ready.mcae-llms-benchmark-reportLLMscore-ICLR-OpenReview
LLMscore-ICLR-OpenReview
This dataset is the released original dataset for the paper Position: Peer
Review Should Be Calibrated via LLM Scoring by Zijin Chen, Lesui Yu, Xiaofei
Liao, Hai Jin, and Qinbin Li. The paper has been accepted to the ICML 2026
Position Track.
Its concrete purpose is peer review analysis: the dataset is meant for
studying how paper-review rationales, numeric ratings, LLM-derived anchor
scores, and review-score residuals interact in scientific peer… See the full description on the dataset page: https://huggingface.co/datasets/Wutaghost/LLMscore-ICLR-OpenReview.multimodal-LLMs-See-Sentiment
MLLMsent — datasets and experiment results
Every input and every output of "Multimodal LLMs See Sentiment"
(arXiv:2508.16873): the image descriptions generated by six multimodal
LLMs, the sentiment labels derived from the PerceptSent annotations, and the complete
per-fold results of all 141 experiments.
Paper: arXiv:2508.16873
Code, training and inference: https://github.com/neemiasbsilva/multimodal-LLMs-see-sentiment
Model checkpoints:… See the full description on the dataset page: https://huggingface.co/datasets/neemiasbsilva/multimodal-LLMs-See-Sentiment.or-bench-toxic-all
OR-Bench: An Over-Refusal Benchmark for Large Language Models
This dataset constains highly toxic prompts, use with caution!!!
Please see our demo at HuggingFace Spaces.
Overall Plots of Model Performances
Below is the overall model performance. X axis shows the rejection rate on OR-Bench-Hard-1K and Y axis shows the rejection rate on OR-Bench-Toxic. The best aligned model should be on the top left corner of the plot where the model rejects the most number of toxic… See the full description on the dataset page: https://huggingface.co/datasets/bench-llms/or-bench-toxic-all.llms-hw2jailbreak-detection-dataset
Jailbreak Detection Dataset (MLCommons-Aligned)
A comprehensive dataset for training AI safety classifiers, aligned with the MLCommons AI Safety taxonomy.
Dataset Description
This dataset combines multiple sources for robust jailbreak and safety detection:
Primary Sources
nvidia/Aegis-AI-Content-Safety-Dataset-2.0: 18,164 samples with MLCommons-aligned labels
lmsys/toxic-chat: Toxic content detection
jackhhao/jailbreak-classification: Jailbreak attack patterns… See the full description on the dataset page: https://huggingface.co/datasets/llm-semantic-router/jailbreak-detection-dataset.llm-similarity-riskllmsplit_4o_mini_decontextualizedllms-journ-sourcing-2025MaliciousInstructReasoning-Boosts-Opinion-Alignment-in-LLMs
Reasoning Boosts Opinion Alignment in LLMs
Download and load with DataDict.load_from_disk.
Dataset fields
id: Identifier for the respondent / party / candidate (see lists below)
question: Identifier for the question
question_text: The actual question
answer: The answer to the respondent / party / candidate gave to the question. A = Yes, B = No, C = Neutral.
answer_comment: The argument / comment used for SFT.
political_position: The ideological group / party for this… See the full description on the dataset page: https://huggingface.co/datasets/disco-eth/Reasoning-Boosts-Opinion-Alignment-in-LLMs.llm-srbench
LLM-SRBench: Benchmark for Scientific Equation Discovery with LLMs
This dataset contains LLM-SRBench, a comprehensive benchmark for evaluating Large Language Models (LLMs) on scientific equation discovery (symbolic regression) tasks.
Paper: LLM-SRBench: A New Benchmark for Scientific Equation Discovery with Large Language Models (ICML 2025 Oral)
Original Repository: deep-symbolic-mathematics/llm-srbench
Original Dataset: nnheui/llm-srbench
📊 Dataset Overview… See the full description on the dataset page: https://huggingface.co/datasets/pkuHaowei/llm-srbench.llmsplit_deepseek_decontextualizedllmsys-hpobench
LLMSYS-HPOBench
LLMSYS-HPOBench is an offline benchmark dataset for hyperparameter optimization of real-world LLM systems. It covers inference engines, RAG pipelines, and agent frameworks, with normalized tabular measurements linked to log and hardware artifacts when available.
Project Links
GitHub repository, benchmark loader, and contribution guide: https://github.com/ideas-labo/llmsys-hpobench
Paper: https://arxiv.org/abs/2605.08305
Full data archive on… See the full description on the dataset page: https://huggingface.co/datasets/KleinWu/llmsys-hpobench.llms.txt
llms.txt files extracted from the Common Crawl corpus
This dataset contains llms.txt files extracted from the Common Crawl corpus.
Specifically, we extracted response records matching */llms.txt and */llms-full.txt with status 200 and MIME-type text/plain or text/markdown.
What is llms.txt?
The /llms.txt file: A proposal to standardise on using an /llms.txt file to provide information to help LLMs use a website at inference time.
Our own analysis of this dataset is available… See the full description on the dataset page: https://huggingface.co/datasets/commoncrawl/llms.txt.LLMsGeneratedCodellm-system-prompts-benchmark
Dataset Card for Dataset Name
This datset is a collection of 100 system prompts for large language models.
Dataset Details
Dataset Description
These 100 system prompts test a model's ability to follow grammatical patterns; answer basic multiple choice questions; act according to a particular persona; memorize information; and speak in French.
Files:
hundred_system_prompts.py: refer to this to see the (prompt, probe, function) triplets, as well as the… See the full description on the dataset page: https://huggingface.co/datasets/Naomibas/llm-system-prompts-benchmark.llmsplit_deepseek