Datasetpublic

ciderlab/judge_prompt_dataset_v1_dedup

Self-Contained Judge Dataset Exported at: 20260602T022100Z This is the Hugging Face Hub-ready form of the judge dataset. It contains parquet shards with embedded prompt-order images and no separate asset tree. Layout train-*-of-*.parquet validation-*-of-*.parquet test-*-of-*.parquet metadata.json README.md Load from datasets import load_dataset ds = load_dataset("Jsonwu/judge_prompt_dataset_v1_dedup") Fields prompt_images stores… See the full description on the dataset page: https://huggingface.co/datasets/ciderlab/judge_prompt_dataset_v1_dedup.

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Dataset Card

Self-Contained Judge Dataset

Exported at: 20260602T022100Z

This is the Hugging Face Hub-ready form of the judge dataset. It contains parquet shards with embedded prompt-order images and no separate asset tree.

Layout

—train-*-of-*.parquet
—validation-*-of-*.parquet
—test-*-of-*.parquet
—metadata.json
—README.md

Load

python

from datasets import load_dataset

ds = load_dataset("Jsonwu/judge_prompt_dataset_v1_dedup")

Fields

—prompt_images stores the exact prompt-order image sequence as embedded images.
—context_image_indices and candidate_image_indices slice prompt_images back into context and candidate groups.
—candidate_order preserves A/B ordering and uses ground_truth_candidate_index as a 0-based index into that list.
—image_inputs records the exact image order, provenance, and crop/fit preprocessing.
—source_path is provenance back to the legacy export tree, not a live path in the Hub repo.

Notes

—The published repo is the recommended artifact for downstream analysis.
—The legacy JSONL + assets/ export remains a staging form only.