Datasets:

rockdu
/

miles-diffusion-datasets

flowgrpo_ocr/                    # OCR-style prompts from flowGRPO
├── train.jsonl                  # 19,653
└── test.jsonl                   # 1,018

flowgrpo_pickscore/              # PickScore prompts from flowGRPO
├── train.jsonl                  # 25,432
└── test.jsonl                   # 2,048

Directory prefixes (flowgrpo_*) record the upstream source so the schema stays clear when more datasets land here later (other reward families, internal prompts, etc.).

Format

Each .jsonl file has one JSON object per line:

{"input": "A close-up of a medicine bottle with a clear, red warning label..."}

UTF-8 encoded (ensure_ascii=False), no escaping for non-ASCII characters.

Usage

hf download --repo-type dataset rockdu/miles-diffusion-datasets \
    --local-dir /root/datasets/miles-diffusion-datasets

python train_diffusion.py \
    --prompt-data /root/datasets/miles-diffusion-datasets/flowgrpo_ocr/train.jsonl \
    --eval-prompt-data ocr_test /root/datasets/miles-diffusion-datasets/flowgrpo_ocr/test.jsonl \
    ...

Provenance

flowgrpo_* directories: extracted from flow_grpo's dataset/{ocr,pickscore}/{train,test}.txt files (one prompt per line) and converted to {"input": prompt} JSONL format.