datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
rendered-wikipedia-english
Dataset Card for Team-PIXEL/rendered-wikipedia-english
Dataset Summary
This dataset contains the full English Wikipedia from February 1, 2018, rendered into images of 16x8464 resolution.
The original text dataset was built from a Wikipedia dump. Each example in the original text dataset contained the content of one full Wikipedia article with cleaning to strip markdown and unwanted sections (references, etc.). Each rendered example contains a subset of one full article.… See the full description on the dataset page: https://huggingface.co/datasets/Team-PIXEL/rendered-wikipedia-english.IconStack-48M-Rendered-Traindna_rendering_processed
DNA-Rendering-Processed Dataset
Project Page | Paper | Code | Model
To enable Diffuman4D model training, we meticulously process the DNA-Rendering dataset by recalibrating camera parameters, optimizing image color correction matrices (CCMs), predicting foreground masks, and estimating human skeletons.
To promote future research in the field of human-centric 3D/4D generation, we have open-sourced our re-annotated labels for the DNA-Rendering dataset in this repo, which includes… See the full description on the dataset page: https://huggingface.co/datasets/krahets/dna_rendering_processed.ramanv-image-real-3d-rendersText-Render-2M
Text Render 2M Dataset
A large-scale dataset containing 2 million text rendering image-text pairs for training generative models to improve text rendering performance.
Dataset Structure
image: Rendered text image in PNG format
text: Corresponding text content
file_name: Original filename
folder_id: Folder identifier
Usage
This dataset is designed for fine-tuning generative models to improve text rendering capabilities.
from datasets import load_dataset… See the full description on the dataset page: https://huggingface.co/datasets/PosterCraft/Text-Render-2M.rendered-bookcorpus
Dataset Card for Team-PIXEL/rendered-bookcorpus
Dataset Summary
This dataset is a version of the BookCorpus available at https://huggingface.co/datasets/bookcorpusopen with examples rendered as images with resolution 16x8464 pixels.
The original BookCorpus was introduced by Zhu et al. (2015) in Aligning Books and Movies: Towards Story-Like Visual Explanations by Watching Movies and Reading Books and contains 17868 books of various genres. The rendered BookCorpus was used… See the full description on the dataset page: https://huggingface.co/datasets/Team-PIXEL/rendered-bookcorpus.transcoda-rendered-row-343k-full-pipeline-v1
Transcoda Rendered Row 343k Full Pipeline v1
Full-page rendered Transcoda row dataset generated from synthetic and random-notation transcriptions.
Target contents: 343113
Accepted contents: 343027
Failed/dropped contents: 86
Renderings per accepted content: 4
Accepted images: 1372108
Source counts: {'random': 99990, 'synth': 243037}
Staging repo: cminst/transcoda-rendered-row-343k-full-pipeline-v1-shards
Each row contains one transcription and four independently rendered page… See the full description on the dataset page: https://huggingface.co/datasets/cminst/transcoda-rendered-row-343k-full-pipeline-v1.daruma-SFT-renderedrendered-wikipedia-8x8-withTextveri-render
VeriRender Benchmark Dataset
Causal consistency verification samples for Vision-Language Models.
Layout
manifest.jsonl ← canonical index (one row per sample)
benchmark.yaml ← config used to generate this release
inconsistent/{domain}/{sample_id}/ ← corrupted evaluation samples
consistent/{domain}/{sample_id}/ ← negative controls (clean images)
Splits
Split
Description
Eval image
inconsistent
Symbolic spec is… See the full description on the dataset page: https://huggingface.co/datasets/VietMedTeam/veri-render.rendered-wikipedia-en-8x8rendered-bookcorpus-16x16amex_render_pairs_v5amex_render_pairs_v3mm_rendered_textnayana-renderedrendered-bookcorpus-8x8-withTextNayanaBench-rendered-splitsvg-rendered
SVG to PNG Rendered Dataset
Dataset Summary
This dataset is a processed version of the svgen-500k-instruct dataset, where SVG images have been converted to PNG format for easier consumption in computer vision and machine learning pipelines. Each successfully converted image maintains the original SVG's visual representation while providing a standardized raster format.
Data Fields
png_processed: Boolean flag indicating whether the conversion was successful… See the full description on the dataset page: https://huggingface.co/datasets/thesantatitan/svg-rendered.render_text_largeomnidocbench-render-compare-parquet
OmniDocBench Render-and-Compare — Parquet Edition
Parquet-shard repackaging of
gt-free-ocr-metrics/omnidocbench-render-compare.
Overview
The pipeline processes each page of OmniDocBench
through a Qwen3.5-122B-A10B OCR model, renders the structured output back
to a PNG via HTML (reconstructed), and compares it against the original
page scan (masked_original) using reference-free visual metrics.
Five OCR extraction variants are provided, each targeting a different subset
of… See the full description on the dataset page: https://huggingface.co/datasets/gt-free-ocr-metrics/omnidocbench-render-compare-parquet.IconStack-48M-Rendered-Devtext_rendering
text_rendering
text_rendering
Trigger token: sks_textrender
Examples: 111
Format: p-image
Source: /Users/davidberenstein/Documents/programming/pruna/dataset-generator/training/text-rendering.zip
Use input.zip with p-image-trainer (Replicate). See TRAINING_PLAN.md in this directory.
Format
Trainer: p-image-trainer
Schema: See config.yml and TRAINING_PLAN.md in this repo.
Reproduce
generate.py in this repo documents how to regenerate this dataset… See the full description on the dataset page: https://huggingface.co/datasets/davidberenstein1957/text_rendering.opencode-public-data-pack-docker_input1-20-renders-512-20260612t125042z
OpenCode Public Data Pack docker_input1 20 renders 512 20260612T125042Z
Public data pack created from docker_input1.json with 20 renders at 512x512.
This dataset mirrors public data-pack render outputs from Physicl.
Each row represents one render view. The image column contains a stable URL to the primary render image uploaded under /data; image_path stores the relative repository path and data_commit_sha pins the Hugging Face dataset commit used by those URLs. Files are… See the full description on the dataset page: https://huggingface.co/datasets/physicl-test/opencode-public-data-pack-docker_input1-20-renders-512-20260612t125042z.sceneteract-renders
SceneTeract Scene Renders
The images a VLM is shown when judging whether an activity is physically feasible in a
3D indoor scene. Pair these with
sceneteract-traces
to evaluate a model against geometry-grounded labels.
3,621 renders over 1,132 3D-FRONT living rooms and dining rooms, 1024×1024 PNG.
from datasets import load_dataset
renders = load_dataset("leopoldmaillard/sceneteract-renders")["train"]
renders[0]["image"] # PIL image
Two kinds of image… See the full description on the dataset page: https://huggingface.co/datasets/leopoldmaillard/sceneteract-renders.gsm8k-rendered-vlm-v2
GSM8K Rendered-VL v2
1319 rendered GSM8K test problems for the VLM modality study (Phase 1).
Contributors
Rodela Ghosh — study design, pilot (v1), dataset packaging and Hugging Face release (scripts/prepare_hf_v2_release.py)
Aviral Gupta — benchmark infrastructure (src/), v2 rendering protocol (src/rendering.py), Phase 1 model runs
Code: https://github.com/Ro-netizen004/vlm-modality-research
Not interchangeable with v1: RodelaG/gsm8k-rendered-vlm
v1
v2… See the full description on the dataset page: https://huggingface.co/datasets/vlm-modality-research/gsm8k-rendered-vlm-v2.svg-rendered-blip_captioned
SVG to PNG Rendered Dataset
Dataset Summary
This dataset is a processed version of the svgen-500k-instruct dataset, where SVG images have been converted to PNG format for easier consumption in computer vision and machine learning pipelines. Each successfully converted image maintains the original SVG's visual representation while providing a standardized raster format.
Data Fields
caption: Image captions generated using Salesforce's BLIP model
png_processed:… See the full description on the dataset page: https://huggingface.co/datasets/thesantatitan/svg-rendered-blip_captioned.pa-warm-start-sft-25b-rendered-review
pa-warm-start-sft-25b rendered review sample (n=200)
200 uniformly-sampled conversations from geodesic-research/pa-warm-start-sft-heavy-25b-mix
(default/train, the control-pretraining 30B baseline SFT corpus), rendered EXACTLY as the
training pack renders them: the library's _chat_preprocess (tool-call normalization +
think-HISTORY chat template + assistant-only loss mask).
Columns: rendered_text (the full string the model sees), trainable_spans_only
(concatenation of… See the full description on the dataset page: https://huggingface.co/datasets/geodesic-research/pa-warm-start-sft-25b-rendered-review.meaningfulness-cross-language-rendering
Cross-Language Rendering for Meaning vs Meaningfulness (Paper B 2026ap)
HF dataset DOI: 10.57967/hf/8971
Companion paper concept DOI: 10.5281/zenodo.20409701
Companion GitHub mirror: https://github.com/spectralbranding/meaningfulness-papers/tree/main/meaning-meaningfulness-empirical
Dataset Summary
This dataset contains the multi-language rendering and extraction artifacts demonstrating Proposition P4 (rendering-equivalence under spine-preservation) from Zharnikov… See the full description on the dataset page: https://huggingface.co/datasets/spectralbranding/meaningfulness-cross-language-rendering.chess_render_360