Add README with viewer configs and dataset documentation

README.md

@@ -0,0 +1,96 @@
+---
+license: apache-2.0
+task_categories:
+  - video-text-to-text
+  - visual-question-answering
+  - image-text-to-text
+language:
+  - en
+tags:
+  - llava
+  - multimodal
+  - video
+  - spatial-reasoning
+size_categories:
+  - 10M<n<100M
+configs:
+  - config_name: viewer_caption_30s
+    data_files:
+      - split: preview
+        path: viewer/caption_30s.parquet
+  - config_name: viewer_caption_60s
+    data_files:
+      - split: preview
+        path: viewer/caption_60s.parquet
+  - config_name: viewer_spatial
+    data_files:
+      - split: preview
+        path: viewer/spatial.parquet
+---
+
+# LLaVA-OneVision-2-Data
+
+Training data for the LLaVA-OneVision-2 multimodal model family, covering large-scale video and spatial reasoning corpora used in mid-training.
+
+## Dataset Composition
+
+| Subset | Format | Description |
+|---|---|---|
+| `mid_training_video/60s_rest/` | WebDataset (`.tar`) | 10,809 shards of ~60s video clips |
+| `mid_training_video/caption_v0/split_30s.jsonl` | JSONL | Captions for 30-second video clips |
+| `mid_training_video/caption_v0/split_60s.jsonl` | JSONL | Captions for 60-second video clips |
+| `spatial/` | WebDataset (`.tar`) | 84 shards of spatial reasoning data (refcoco, visual genome, pointing, 3D, etc.) |
+
+## Preview Configs
+
+The three `viewer_*` configs above expose small Parquet samples so the Hugging Face Dataset Viewer can render the data directly in the browser:
+
+- **`viewer_caption_30s`** — 5 caption samples from 30-second clips
+- **`viewer_caption_60s`** — 5 caption samples from 60-second clips
+- **`viewer_spatial`** — 10 spatial-reasoning samples with embedded thumbnail images, mixed across tasks (refcoco, visual genome, pointing, ca1m, osd, crosspoint, erqa, roborefer)
+
+These previews are intended for **schema inspection only**. For training, use the full `mid_training_video/` and `spatial/` shards.
+
+## Loading Examples
+
+### Stream the full spatial WebDataset
+```python
+from datasets import load_dataset
+
+ds = load_dataset(
+    "mvp-lab/LLaVA-OneVision-2-Data",
+    data_files="spatial/train_*.tar",
+    split="train",
+    streaming=True,
+)
+for sample in ds:
+    print(sample)
+    break
+```
+
+### Load a viewer preview
+```python
+from datasets import load_dataset
+
+ds = load_dataset("mvp-lab/LLaVA-OneVision-2-Data", "viewer_spatial", split="preview")
+print(ds[0])
+```
+
+## Schema
+
+### Caption (`viewer_caption_30s`, `viewer_caption_60s`)
+- `images_source: List[str]` — relative paths to source video files
+- `messages: List[{role, content}]` — chat-format caption prompt and assistant response
+- `preview: str` — flattened text preview
+
+### Spatial (`viewer_spatial`)
+- `id: str` — sample id
+- `task: str` — source task name (e.g. `refcoco`, `visual_genome`, `pointing`)
+- `image: Image` — first referenced image, embedded as JPEG bytes (downscaled to max edge 1024)
+- `image_paths: List[str]` — original relative image paths in the full dataset
+- `messages: List[{role, content}]` — chat-format Q/A
+- `preview: str` — flattened text preview
+
+## License
+
+Apache 2.0