datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
WebCompass
WebCompass
A unified multimodal benchmark for evaluating LLMs' ability to generate, edit, and repair functional web pages. WebCompass spans three input modalities — text design documents, reference screenshots, and video demonstrations — and three task families — generation, editing, and repair.
GitHub: NJU-LINK/WebCompass
Project Page: nju-link.github.io/WebCompass
Quick Start
from datasets import load_dataset
# Generation tasks (existing)
ds_text =… See the full description on the dataset page: https://huggingface.co/datasets/NJU-LINK/WebCompass.3DHarnessBench
Probing Agentic 3D-to-Code Capabilities of Frontier Vision-Language Models
Project Page
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GitHub
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Arxiv
Abstract
3DHarnessBench evaluates the agentic capacity of frontier vision-language models (VLMs) to recover 3D geometry as executable Blender Python code from multiple forms of target evidence. Rather than restricting every system to a single fixed input, the benchmark compares four progressively richer harnesses: Single-view, Multi-view, Active… See the full description on the dataset page: https://huggingface.co/datasets/lingada/3DHarnessBench.ramanv-image-editing
ramanv-image-editing
Image editing dataset for training FLUX.1-Kontext / InstructPix2Pix style models.
Size
592,141 total editing pairs
Sources: ultraedit
Schema
Each shard tar contains {uid}_src.jpg, {uid}_edit.jpg, {uid}_mask.png (where available).
Metadata per record: instruction, prompt, edit_type, caption_before/after, license, sha256.
Licenses
MagicBrush, InstructPix2Pix, Pico-Banana, HumanEdit: CC-BY-4.0
UltraEdit, AnyEdit… See the full description on the dataset page: https://huggingface.co/datasets/lingamvamshikrishnareddy/ramanv-image-editing.nepali-synthetic-ocr-lines
Nepali Synthetic OCR/HTR Document Line Dataset
A dataset of synthetic Devanagari text line images imitating historical and official scanned document conditions, designed for OCR (Optical Character Recognition) and HTR (Handwritten Text Recognition) models such as TrOCR, CRNN, and PaddleOCR.
This dataset was generated using the Mountmind PeakOCR Studio synthetic corpus generator pipeline, introducing realistic document aging artifacts like:
Skew Angle Rotations (Hough line… See the full description on the dataset page: https://huggingface.co/datasets/prashant0919/nepali-synthetic-ocr-lines.pixmo_images_badlines_hu_v5benchDrive