| # miles-diffusion-datasets |
|
|
| Prompt datasets used by the miles-diffusion training pipeline. |
|
|
| ## Layout |
|
|
| ``` |
| 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 |
| |
| hpdv2/ # Deduplicated prompts from HPDv2 |
| ├── train.jsonl # 103,672 |
| └── test.jsonl # 242 |
| ``` |
|
|
| Directory names 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: |
|
|
| ```json |
| {"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 |
|
|
| ```bash |
| 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](https://github.com/yifan123/flow_grpo)'s |
| `dataset/{ocr,pickscore}/{train,test}.txt` files (one prompt per line) and |
| converted to `{"input": prompt}` JSONL format. |
|
|
| `hpdv2/`: extracted from the `prompt` field of |
| [`ymhao/HPDv2`](https://huggingface.co/datasets/ymhao/HPDv2) at revision |
| `bb0f2563e451e11c3f376b2ba93615db00e042e1`. Prompts are stripped, empty or |
| non-string values are dropped, and each source split is deduplicated while |
| preserving first occurrence. Prompts present in `train` are removed from |
| `test`, leaving no cross-split overlap. The source dataset is licensed under |
| Apache-2.0; please cite the original |
| [HPSv2 paper](https://arxiv.org/abs/2306.09341) when using these prompts. |
|
|
