datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Bitext-customer-support-llm-chatbot-training-dataset
Bitext - Customer Service Tagged Training Dataset for LLM-based Virtual Assistants
Overview
This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the Customer Support sector can be easily achieved using our two-step approach to LLM… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-customer-support-llm-chatbot-training-dataset.cyp-challenge-train-test
CYP Challenge Train/Test Dataset
A high-quality experimental dataset for predicting inhibition of the major drug-metabolizing Cytochrome P450 enzymes (CYP1A2, CYP2C9, CYP2D6, CYP3A4), released as part of the OpenADMET CYP Inhibition Blind Challenge.
Blog post: Announcing OpenADMET’s CYP inhibition blind challenge
Challenge Space: OpenADMET CYP Inhibition Blind Challenge
Challenge period: August 17, 2026 - November 3, 2026
Produced by: OpenADMET
CHANGELOG
Updated… See the full description on the dataset page: https://huggingface.co/datasets/openadmet/cyp-challenge-train-test.pxr-challenge-train-test
PXR Challenge Train/Test Dataset
A high-quality experimental dataset for predicting human Pregnane-X Receptor (PXR) induction, comprising over 11,000 compounds screened using a high-fidelity in-house assay. This is the largest publicly available PXR activity dataset, released as part of the OpenADMET PXR Induction Blind Challenge.
Blog post: Announcing the Next OpenADMET Blind Challenge: Predicting PXR Induction
Challenge Space: openadmet/pxr-challenge
Challenge period: April 1… See the full description on the dataset page: https://huggingface.co/datasets/openadmet/pxr-challenge-train-test.MMLU-Pro-CoT-Train-Labeled
Dataset Details
Modality: Text
Format: CSV
Size: 10K - 100K rows
Total Rows: 84,098
License: MIT
Libraries Supported: datasets, pandas, croissant
Structure
Each row in the dataset includes:
question: The query posed in the dataset.
answer: The correct response.
category: The domain of the question (e.g., math, science).
src: The source of the question.
id: A unique identifier for each entry.
chain_of_thoughts: Step-by-step reasoning steps leading to the answer.
labels:… See the full description on the dataset page: https://huggingface.co/datasets/UW-Madison-Lee-Lab/MMLU-Pro-CoT-Train-Labeled.Bitext-retail-ecommerce-llm-chatbot-training-dataset
Bitext - Retail (eCommerce) Tagged Training Dataset for LLM-based Virtual Assistants
Overview
This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the [Retail (eCommerce)] sector can be easily achieved using our two-step approach to LLM… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-retail-ecommerce-llm-chatbot-training-dataset.plant-disease-trainopenadmet-expansionrx-challenge-train-data
OpenADMET-ExpansionRx Challenge training dataset
This dataset contains real-work ADMET data from a recently prosecuted series of drug discovery campaigns by Expansion Therapeutics on RNA mediated diseases. While optimising candidate molecules for their preclinical programs Expansion collected a variety of ADMET data for off-targets and properties of interest in the traditional game of “whack-a-mole” familiar to all drug hunters. Now, they’ve made the bold and generous decision to… See the full description on the dataset page: https://huggingface.co/datasets/openadmet/openadmet-expansionrx-challenge-train-data.pizza_st_human_mouse_v1_train_with_labelsBitext-events-ticketing-llm-chatbot-training-dataset
Bitext - Events and Ticketing Tagged Training Dataset for LLM-based Virtual Assistants
Overview
This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the [events and ticketing] sector can be easily achieved using our two-step approach to LLM… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-events-ticketing-llm-chatbot-training-dataset.FARM_training_test
FARM Aerial Radio Map (ARM) Dataset
Paper:
FARM: Foundational Aerial Radio Map for Intelligent Low-Altitude Networking (https://arxiv.org/abs/2604.17362)
Overview
This repository releases the constructed ARM datasets based on ARM-Omni for FARM training, in-domain evaluation (D1-D10), and zero-shot evaluation (P1, F1, and A1). The dataset coverage is summarized below:
Dataset
Frequencies (GHz)
Max Rx Height (m)
Beamwidths
Map Grid Size
Volume
D1
2.1… See the full description on the dataset page: https://huggingface.co/datasets/jliang097/FARM_training_test.MUG-V-Training-Samples
MUG-V Training Samples
Sample training dataset for the MUG-V 10B video generation model training framework.
Dataset Description
This dataset contains pre-processed training samples for quick-start validation and testing of the MUG-V Megatron-LM training pipeline. It includes:
VideoVAE-encoded latents (8×8×8 compressed video representations)
T5-XXL text features (4096-dim embeddings)
Training metadata CSV (sample mapping and configuration)
⚠️ Note: This is a sample… See the full description on the dataset page: https://huggingface.co/datasets/MUG-V/MUG-V-Training-Samples.STARCOP_allbands_Train1
STARCOP dataset
STARCOP dataset: Semantic Segmentation of Methane Plumes with Hyperspectral Machine Learning Models 🌈🛰️Authors: Vít Růžička, Gonzalo Mateo-Garcia, Luis Gómez-Chova, Anna Vaughan, Luis Guanter and Andrew Markham
Fast data preview in: dataset_exploration.ipynb Main repository: github/spaceml-org/STARCOP
Task:
Methane is the second most important greenhouse gas contributor to climate change; at the same time its reduction has been denoted as one of the… See the full description on the dataset page: https://huggingface.co/datasets/previtus/STARCOP_allbands_Train1.Dream_TrainBitext-insurance-llm-chatbot-training-dataset
Bitext - Insurance Tagged Training Dataset for LLM-based Virtual Assistants
Overview
This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the [insurance] sector can be easily achieved using our two-step approach to LLM Fine-Tuning. An… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-insurance-llm-chatbot-training-dataset.FrontierCO-TrainReverse-hybrid-train-no-persona-meanBitext-telco-llm-chatbot-training-dataset
Bitext - Telco Tagged Training Dataset for LLM-based Virtual Assistants
Overview
This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the [telco] sector can be easily achieved using our two-step approach to LLM Fine-Tuning. An overview of… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-telco-llm-chatbot-training-dataset.Bitext-travel-llm-chatbot-training-dataset
Bitext - Travel Tagged Training Dataset for LLM-based Virtual Assistants
Overview
This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the [Travel] sector can be easily achieved using our two-step approach to LLM Fine-Tuning. An overview of… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-travel-llm-chatbot-training-dataset.Reverse-hybrid-correct-train-no-persona-meanDeepSeek-R1-Distill-Qwen-32B_NUMINA_train_amc_aime-llama3.1Original-hybrid-correct-train-no-persona-meantripclick-training
TripClick Baselines with Improved Training Data
Establishing Strong Baselines for TripClick Health Retrieval Sebastian Hofstätter, Sophia Althammer, Mete Sertkan and Allan Hanbury
https://arxiv.org/abs/2201.00365
tl;dr We create strong re-ranking and dense retrieval baselines (BERTCAT, BERTDOT, ColBERT, and TK) for TripClick (health ad-hoc retrieval). We improve the – originally too noisy – training data with a simple negative sampling policy. We achieve large gains over BM25 in the… See the full description on the dataset page: https://huggingface.co/datasets/sebastian-hofstaetter/tripclick-training.OmniVCus-Train
[NeurIPS 2025] OmniVCus: Feedforward Subject-driven Video Customization with Multimodal Control Conditions
Dataset Description
This dataset supports multi-modal constrol video generation. It contains ~80K data samples processed from 140K videos by our VideoCus-Factory pipeline. Each data sample includes the original
video, text prompts, subject reference image, depth video, mask video, and motion video conditions.
Here is a data example:
Generated… See the full description on the dataset page: https://huggingface.co/datasets/CaiYuanhao/OmniVCus-Train.Original-hybrid-train-no-persona-meantraining_dataxnli2.0_train_arabicROCOv2-trainpii_train
Russian PII NER Training Dataset
Dataset Description
This is the training corpus for PII (Personally Identifiable Information)
detection and Named Entity Recognition (NER) on Russian-language text. It
targets guardrail and anonymization pipelines that must reliably find personal
data (names, addresses, contacts) and Russian identity-document numbers
(passport, SNILS, INN, OMS, etc.) in text.
The corpus combines real, manually annotated examples from production… See the full description on the dataset page: https://huggingface.co/datasets/redmadrobot-rnd/pii_train.SC-train-valid-test_SDG-Descriptionsnli-label:
(0) entailment
(2) contradiction
Bitext-mortgage-loans-llm-chatbot-training-dataset
Bitext - Mortgage and Loans Tagged Training Dataset for LLM-based Virtual Assistants
Overview
This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the [Mortgage and Loans] sector can be easily achieved using our two-step approach to LLM… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-mortgage-loans-llm-chatbot-training-dataset.