datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
explicit-edit-benchmark
Explicit Edit Benchmark
226 deterministic exact-edit tasks, run by different agents, harnesses, models and configurations. Every observation records what the harness did and whether the resulting files matched byte for byte.
Source code and benchmark runner: GitHub — Explicit Edit Benchmark
Open the interactive Explorer to compare agents, harnesses, models, versions, reasoning modes, correctness, recovery, time, cost and tokens.
Leaderboard by model route
Score v2… See the full description on the dataset page: https://huggingface.co/datasets/alexshpunt/explicit-edit-benchmark.Inter-Edit-Train
Inter-Edit-Train
Inter-Edit-Train is the official large-scale training set released for the CVPR 2026 paper Inter-Edit: First Benchmark for Interactive Instruction-Based Image Editing.
This dataset is designed for the Interactive Instruction-based Image Editing (I^3E) task, where a model performs localized image edits from a concise textual instruction together with imprecise spatial guidance.
Highlights
1,099,964 image editing pairs
610,186 unique source images
Four… See the full description on the dataset page: https://huggingface.co/datasets/a1557811266/Inter-Edit-Train.SEED-Data-Edit-Part1-Openimages
SEED-Data-Edit
SEED-Data-Edit is a hybrid dataset for instruction-guided image editing with a total of 3.7 image editing pairs, which comprises three distinct types of data:
Part-1: Large-scale high-quality editing data produced by automated pipelines (3.5M editing pairs).
Part-2: Real-world scenario data collected from the internet (52K editing pairs).
Part-3: High-precision multi-turn editing data annotated by humans (95K editing pairs, 21K multi-turn rounds with a maximum of 5… See the full description on the dataset page: https://huggingface.co/datasets/AILab-CVC/SEED-Data-Edit-Part1-Openimages.dockersv1MMH3_Image_Edit_WorkflowThis is just an example of using MiniMax H3 as an image editor. The actual workflow that I use requires several custom nodes, some of which are not published, so this one is simply a bare bones demonstration.
This uses the hybrid MiniMax H3 model from here: https://huggingface.co/smhfacct/Minimax-H3-fl2va-ref2va-hybrid-models/tree/main
It uses the custom VAE from here: https://huggingface.co/Mamad8/MiniMax-H3-Image-VAE/tree/main
It uses the LoRA from here:… See the full description on the dataset page: https://huggingface.co/datasets/fizzlepoof/MMH3_Image_Edit_Workflow.OralGPT-X-Editsynthetic-commit-msg-edits
✍️ Commit Message Edits Dataset - 🤖Synthetic
This dataset is a synthetic extension of our expert-labeled commit message edits dataset presented in Towards Realistic Evaluation of Commit Message Generation by Matching Online and Offline Settings.
You can check Synthetic tab in our visualization app to browse through the datapoints!
Dataset Structure
Default
Default split contains the synthetic messages generated from expert-labeled dataset by an LLM.… See the full description on the dataset page: https://huggingface.co/datasets/JetBrains-Research/synthetic-commit-msg-edits.foi-ca-federal-atip
Canada federal ATI nil-return archive
This dataset contains the public, non-personal institutional nil-return summary
published by the Government of Canada Open Government Portal.
index.jsonl is the Dataset Viewer data file. ati-nil.csv is the preserved
source original. manifest.json records the public package hashes and is
documentation, not a second data table.
Source licence: Open Government Licence – Canada.
Attribution: Contains information licensed under the Open… See the full description on the dataset page: https://huggingface.co/datasets/edithatogo/foi-ca-federal-atip.Edit-Reviewluxury-watch-editorial-dataset-v1
license: apache-2.0
tags:
- watch-editorial
- luxury-watches
- fine-tuning
- instruction-tuning
- horological
language: en
size_categories:
- 100<n<1K
SWELOL Luxury Watch Editorial Dataset v1
Dataset Description
High-quality human-annotated luxury watch editorial descriptions for fine-tuning language models. Created by sweelol for production-grade watch content generation.
Version: 1.0License: Apache 2.0Total Examples: 308 (44 original + 264… See the full description on the dataset page: https://huggingface.co/datasets/sweelol/luxury-watch-editorial-dataset-v1.peer_wiki-edits-mix
WikiEditsMix Task from the PEER Benchmark (Performance Evaluation of Edit Representations)
Description from the benchmark paper:
We randomly selected 20 of the 200 most edited Wikipedia articles and extracted the diff for each revision using the WikiMedia API. We make use of Wikimedia’s ORES (Halfaker and Geiger 2020) API and scrape the draftquality label for each revision. There are 4 draftquality labels: spam, vandalism, attack, and OK, each corresponding to a different quality… See the full description on the dataset page: https://huggingface.co/datasets/jvamvas/peer_wiki-edits-mix.editable-sketch-repro-resultsInter-Edit-Train
Inter-Edit-Train
Inter-Edit-Train is the official large-scale training set released for the CVPR 2026 paper Inter-Edit: First Benchmark for Interactive Instruction-Based Image Editing.
This dataset is designed for the Interactive Instruction-based Image Editing (I^3E) task, where a model performs localized image edits from a concise textual instruction together with imprecise spatial guidance.
Highlights
1,099,964 image editing pairs
610,186 unique source images… See the full description on the dataset page: https://huggingface.co/datasets/dendiofskyez/Inter-Edit-Train.retro-weave-agent-editor-repair-diffs-v0.1
RetroInstruct Weave Agent Editor Repair Diffs
This component of RetroInstruct trains weave-agent to use the WeaveEditor to fix synthetic corruptions in the vein of
the Easy Prose Repair Diffs component.
Each row in the dataset provides the pieces you need to make a synthetic episode
demonstrating the agent:
Singling out one of three files as corrupted and in need of repair
Writing out a patch to the file as either a series of WeaveEditor edit() commands or a unidiff
Observing the… See the full description on the dataset page: https://huggingface.co/datasets/jdpressman/retro-weave-agent-editor-repair-diffs-v0.1.editable-sketch-repro-results-final
Scaled FormalMath-Lite reproduction for paper mI3K0e1KsN
This repository contains the machine-verification output from an independent,
scaled reproduction of Editable Proof Sketch for Automated Theorem Proving.
It is not a benchmark-scale estimate of the paper's reported 76.0% pass rate.
Valid run
Benchmark: SphereLab/FormalMATH-Lite (8 deterministic examples out of 425,
seed 2022)
Generator: deepseek-ai/DeepSeek-Prover-V2-7B
Verifier: Lean 4.11.0 with Mathlib… See the full description on the dataset page: https://huggingface.co/datasets/Sugutt/editable-sketch-repro-results-final.ori_and_the_blind_forest_definitive_edition_recordings_02
奥日与黑暗森林 raw recordings
This dataset contains raw game recordings managed by Game Data Platform. Access requests require manual approval.
Game ID: game_aed7da6cab294e72cbf63e1b6ad211ee
Collection: general (泛数据)
Recordings: 4
Layout: recordings/<recording_id>/<raw component>
oa-df-x1000-editededitable-sketch-repro-canary