datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
ditditec-wdn--
Dataset Card for DiTEC-WDN
Dataset Summary
DiTEC-WDN Dataset consists of 36 Water Distribution Networks (WDNs). Each network has unique 1,000 scenarios with distinct characteristics.
Scenario represents a timeseries of directed shared-topology graphs, referred to as states or snapshots. In terms of graph-ml, it can be seen as a spatiotemporal graph where nodes and edges are multivariate time series.
A node can represent a reservoir, junction, or tank, while an edge… See the full description on the dataset page: https://huggingface.co/datasets/rugds/ditec-wdn.ditec-wdn--
Dataset Card for DiTEC-WDN
Dataset Summary
DiTEC-WDN Dataset consists of 36 Water Distribution Networks (WDNs). Each network has unique 1,000 scenarios with distinct characteristics.
Scenario represents a timeseries of directed shared-topology graphs, referred to as states or snapshots. In terms of graph-ml, it can be seen as a spatiotemporal graph where nodes and edges are multivariate time series.
A node can represent a reservoir, junction, or tank, while an edge… See the full description on the dataset page: https://huggingface.co/datasets/Dihaw00/ditec-wdn.ditec-wdn--
Dataset Card for DiTEC-WDN
Dataset Summary
DiTEC-WDN Dataset consists of 36 Water Distribution Networks (WDNs). Each network has unique 1,000 scenarios with distinct characteristics.
Scenario represents a timeseries of directed shared-topology graphs, referred to as states or snapshots. In terms of graph-ml, it can be seen as a spatiotemporal graph where nodes and edges are multivariate time series.
A node can represent a reservoir, junction, or tank, while an edge… See the full description on the dataset page: https://huggingface.co/datasets/hulaba/ditec-wdn.Ditto-1M
Ditto-1M: A High-Quality Synthetic Dataset for Instruction-Based Video Editing
Ditto: Scaling Instruction-Based Video Editing with a High-Quality Synthetic Dataset
Qingyan Bai, Qiuyu Wang, Hao Ouyang, Yue Yu, Hanlin Wang, Wen Wang, Ka Leong Cheng, Shuailei Ma, Yanhong Zeng, Zichen Liu, Yinghao Xu, Yujun Shen, Qifeng Chen
Figure: Our proposed synthetic data generation pipeline can automatically produce high-quality and highly diverse video editing data, encompassing both… See the full description on the dataset page: https://huggingface.co/datasets/QingyanBai/Ditto-1M.ditec-wdn--
Dataset Card for DiTEC-WDN
Dataset Summary
DiTEC-WDN Dataset consists of 36 Water Distribution Networks (WDNs). Each network has unique 1,000 scenarios with distinct characteristics.
Scenario represents a timeseries of directed shared-topology graphs, referred to as states or snapshots. In terms of graph-ml, it can be seen as a spatiotemporal graph where nodes and edges are multivariate time series.
A node can represent a reservoir, junction, or tank, while an edge… See the full description on the dataset page: https://huggingface.co/datasets/jattcoder00/ditec-wdn.DiTFakeHere is the released dataset (DiTFake) for Synthetic Image Detection (SID) proposed in our paper.
Improving Synthetic Image Detection Towards Generalization: An Image Transformation Perspective
This dataset contains 30,000 images in total, including synthetic images generated by three recent DiT-based models (Flux, PixArt, and SD3) and equal numbers of real images from COCO.
More implementation details can be found in our GitHub repository.
ditec-wdn--
Dataset Card for DiTEC-WDN
Dataset Summary
DiTEC-WDN Dataset consists of 36 Water Distribution Networks (WDNs). Each network has unique 1,000 scenarios with distinct characteristics.
Scenario represents a timeseries of directed shared-topology graphs, referred to as states or snapshots. In terms of graph-ml, it can be seen as a spatiotemporal graph where nodes and edges are multivariate time series.
A node can represent a reservoir, junction, or tank, while an edge… See the full description on the dataset page: https://huggingface.co/datasets/razaali10/ditec-wdn.video-dit-latents-hq
Video DiT Latents - Animals (HQ)
Pre-computed VAE latents for training video generation models.
Dataset Info
Property
Value
Resolution
256×256 pixels
Latent Shape
(4, 16, 32, 32)
Frames
16 @ 8fps (2 seconds)
VAE
stabilityai/sd-vae-ft-mse
Classes
dog, cat, bird, horse, fish, lion, elephant, monkey, butterfly, deer
Usage
import torch
from pathlib import Path
# Load a single latent
latent = torch.load("dog/12345.pt")… See the full description on the dataset page: https://huggingface.co/datasets/Jnaranjo/video-dit-latents-hq.dit-loras-interpreting
andyx10/dit-loras-interpreting
Experimenting with interpreting write vectors over 100 hidden-topic model organisms fromdiff-interpretation-tuning/loras
implementation
We use 'self_attn.o_proj andmlp.down_proj` for write vectors: two per block across 36 blocks, with a total of 72 write vectors per organism.
Jacobian Lens from Neuronpedia
neuronpedia/jacobian-lens
(qwen3-4b/jlens/Salesforce-wikitext/Qwen3-4B_jacobian_lens.pt)
layout
test100/… See the full description on the dataset page: https://huggingface.co/datasets/andyx10/dit-loras-interpreting.Ditto_emo_checkpoint_loss_200ditto_localzangei-dit-stage-1-250k-256px-dinov3
Zangei 256px DINOv3 Features — Repacked
Repacked from the known Colab extraction layout.
Source dataset: kingsidharth/zangei-dit-stage-1-250k-256px-img
Feature model: DINOv3 ViT-S/16
Image variants:
resized
square
Feature kinds:
cls
reg
patch
Files:
shards/dinov3_vits16_256_.safetensors
Matching row index:
shards/dinov3_vits16_256_.parquet
Tensor keys:
cls
reg
patch
Manifests:
manifests/files.parquet
manifests/files.csv
config.json
ditto_local_refditto_global_freeform3DiTFakeHere is the released dataset (DiTFake) for Synthetic Image Detection (SID) proposed in our paper.
Improving Synthetic Image Detection Towards Generalization: An Image Transformation Perspective
This dataset contains 30,000 images in total, including synthetic images generated by three recent DiT-based models (Flux, PixArt, and SD3) and equal numbers of real images from COCO.
More implementation details can be found in our GitHub repository.
ditto-source-videosFrom this video editing dataset all source video, but in parquet
DitingBench
Diting Benchmark
Our paperGithub
Our benchmark is designed to evaluate the speech comprehension capabilities of Speech LLMs. We tested both humans and Speech LLMs in terms of speech understanding and provided further analysis of the results, along with a comparative study between the two. This offers insights for the future development of Speech LLMs. For more details, please refer to our paper.
Result
Level
Task
Human Baseline
GPT-4o
MuLLaMA
GAMA
SALMONN… See the full description on the dataset page: https://huggingface.co/datasets/FreedomIntelligence/DitingBench.Cinematic-DiT-Video-Dataset
Cinematic DiT Video Dataset
This dataset is publicly downloadable under a restricted research license. It
is intended for non-commercial research on AI-generated video detection, media
forensics, authenticity analysis, and content-safety evaluation.
Dataset Summary
This dataset contains 9,000 synthetic text-to-video samples generated from
3,000 Chinese cinematic prompts. Each source prompt has one video in each of
three generation profiles. The prompt pipeline… See the full description on the dataset page: https://huggingface.co/datasets/Tsu7am1/Cinematic-DiT-Video-Dataset.low-high-ditto-codebook-analysisMOB-DiT-data
MOB DiT multimodal data
Private transfer repository for mouse olfactory-bulb multimodal spatial data.
Layout
raw/MOB_722/: complete copy of /home/songzq/SMulRe/data/MOB_722.
processed/code_MOB_23/: the eight input artifacts used by DiT_224_Multimodal_MOB.py and DiT_MOB_CellInfo_vali_final.py.
The processed inputs contain Visium and ISS/Xenium-style expression objects, aligned transcript and cell coordinates, morphology fields, gene embeddings, cluster-affinity… See the full description on the dataset page: https://huggingface.co/datasets/JOHNNY2026sadf/MOB-DiT-data.dit-latents-cache3Ditto_emo_checkpoint_200PtychoFlow_DiT
PtyRAD reconstruction eval on generated test split
This folder contains PtyRAD reconstructions for a seeded random subset of test samples pooled from multiple HDF5 files.
Dataset files
simulation_data1.hdf5: /gpfs/scratch/ailab/ai4physic/gendata3/simulation_data1.hdf5
simulation_data2.hdf5: /gpfs/scratch/ailab/ai4physic/gendata3/simulation_data2.hdf5
simulation_data3.hdf5: /gpfs/scratch/ailab/ai4physic/gendata3/simulation_data3.hdf5
simulation_data4.hdf5:… See the full description on the dataset page: https://huggingface.co/datasets/Chocopy/PtychoFlow_DiT.MMFace-DiT-Datasets
MMFace-DiT Dataset: Multimodal Face Generation Benchmarks
This repository contains the multimodal conditioning data and high-quality captions for MMFace-DiT, accepted to CVPR 2026. This dataset provides the necessary spatial (masks, sketches) and semantic (VLM-enriched captions) pairs to enable high-fidelity, controllable face synthesis.
📂 Dataset Components
The dataset is organized to be plug-and-play with the MMFace-DiT repository:
Celeb_Dataset/:… See the full description on the dataset page: https://huggingface.co/datasets/BharathK333/MMFace-DiT-Datasets.ditflow_drawer_vision_only_v1_evalThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "franka",
"total_episodes": 26,
"total_frames": 11562,
"total_tasks": 1,
"total_videos": 78,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 15,
"splits": {
"train": "0:26"},
"data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/danielsanjosepro/ditflow_drawer_vision_only_v1_eval.reflect-dit-train-images
Reflect-DiT Training Images
This is the official dataset repository for the training images used in Reflect-DiT, a Reflective Diffusion Transformer for image generation.
🔗 Paper: Reflect-DiT: Inference-Time Scaling for Text-to-Image Diffusion Transformers via In-Context Reflection
Contents
The dataset is stored in multiple .tar archives located in the data/ directory:
data/
├── gen_eval_sana_part_0.tar
├── gen_eval_sana_part_1.tar
├── ...
└── gen_eval_sana_part_9.tar… See the full description on the dataset page: https://huggingface.co/datasets/KonstantinosKK/reflect-dit-train-images.scatter_ditreflect-DiTrollout_eval_multi_task_dit_frazier_v2_20260907_124913This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 30,
"features": {
"action": {
"dtype": "float32",
"names": [
"shoulder_pan.pos",
"shoulder_lift.pos",
"elbow_flex.pos",
"wrist_flex.pos",
"wrist_roll.pos",
"gripper.pos"
],
"shape": [
6… See the full description on the dataset page: https://huggingface.co/datasets/seriintan/rollout_eval_multi_task_dit_frazier_v2_20260907_124913.