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index bed0738c7eeb449bca98b5d2f33c89a1ee56349a..e02616966d95aede26c3f160c64daab01bba75de 100644
--- a/.gitattributes
+++ b/.gitattributes
@@ -58,3 +58,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+media_index.tsv filter=lfs diff=lfs merge=lfs -text
diff --git a/README.md b/README.md
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index 0000000000000000000000000000000000000000..0942355d471b98d41ee2f60998d5b695ed90ee28
--- /dev/null
+++ b/README.md
@@ -0,0 +1,56 @@
+---
+license: other
+license_name: mixed-source
+task_categories: [image-text-to-text, video-text-to-text]
+tags: [multimodal, reasoning, sft, rl, distillation, mopd]
+configs:
+- config_name: sft_imgr
+  data_files: sft_v4/imgr/*.jsonl
+- config_name: sft_imgp
+  data_files: sft_v4/imgp/*.jsonl
+- config_name: sft_vid
+  data_files: sft_v4/vid/*.jsonl
+- config_name: rl_imgr
+  data_files: rl_v2/imgr.parquet
+- config_name: rl_imgp
+  data_files: rl_v2/imgp.parquet
+- config_name: rl_vid
+  data_files: rl_v2/vid.parquet
+---
+
+# MOPD training data (SFT v4 + RL v2, full media)
+
+The data that trains the MOPD domain teachers on Qwen3.5-9B: one SFT set and one RL prompt set per domain
+(`imgr` image reasoning, `imgp` image perception, `vid` video).
+
+| Split | Rows | Format | Media |
+|---|---|---|---|
+| `sft_v4/imgr` | 1,022,304 | chat jsonl (`messages`, `meta`) | images in `media/` |
+| `sft_v4/imgp` | 1,456,403 | chat jsonl | images in `media/` |
+| `sft_v4/vid` | 710,735 | chat jsonl | videos in `media/` |
+| `rl_v2/imgr` | 64,307 | verl parquet (`prompt`, `images`, `reward_model.ground_truth`, `extra_info`) | images embedded (bytes) |
+| `rl_v2/imgp` | 67,915 | verl parquet | images embedded (bytes) |
+| `rl_v2/vid` | 60,805 | verl parquet | videos in `media/` |
+
+**SFT rows**: single-turn multimodal questions pooled from public datasets; the assistant turn is a reasoning trace
+(`<think>...</think>` + answer, final answer in `\boxed{}`) written by Qwen3.8-Flash-Next with the gold answer given,
+then filtered by agreement with the gold. `meta` keeps the source card, task type and generator.
+**RL rows**: prompts with a rule-checkable gold answer (`reward_model.ground_truth`, `extra_info.task_type`), decontaminated
+against our eval benchmarks.
+
+## Media
+
+65 store-only zip shards in `media_zips/` (523 GB). Unzip all at the repo root:
+
+```bash
+huggingface-cli download ngqtrung/mopd-data --repo-type dataset --local-dir mopd-data
+cd mopd-data && for z in media_zips/*.zip; do unzip -q -n "$z"; done   # -> media/<group>/...
+```
+Every media path in the rows is relative to the repo root (`media/...`). `media_index.tsv` lists path, bytes and shard.
+Media processing used in training: images 65,536-1,605,632 px; videos 1 fps, 4-150 frames, ≤ 65,536 px per frame.
+
+## Sources and license
+
+The questions and media come from public datasets (e.g. LLaVA-Video-178K, FineVideo, Vript, VideoRFT, LLaVA-OneVision,
+and others listed in `meta.card_id`). Each source keeps its own license; check it before use. The reasoning traces are
+model-generated. Released for research.
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