Super-squash branch 'main' using huggingface_hub

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+*.pcm filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+license: other
+tags:
+- cua-lite
+- gui
+- sft
+task_categories:
+- image-text-to-text
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path:
+    - "*/*/train*parquet"
+    - "*/*/train/*.parquet"
+    - "*/*/train/*/*.parquet"
+  - split: validation
+    path:
+    - "*/*/validation*parquet"
+    - "*/*/validation/*.parquet"
+    - "*/*/validation/*/*.parquet"
+- config_name: mobile.navigation
+  data_files:
+  - split: train
+    path:
+    - "mobile/navigation/train*parquet"
+    - "mobile/navigation/train/*.parquet"
+    - "mobile/navigation/train/*/*.parquet"
+  - split: validation
+    path:
+    - "mobile/navigation/validation*parquet"
+    - "mobile/navigation/validation/*.parquet"
+    - "mobile/navigation/validation/*/*.parquet"
+- config_name: mobile.understanding
+  data_files:
+  - split: train
+    path:
+    - "mobile/understanding/train*parquet"
+    - "mobile/understanding/train/*.parquet"
+    - "mobile/understanding/train/*/*.parquet"
+  - split: validation
+    path:
+    - "mobile/understanding/validation*parquet"
+    - "mobile/understanding/validation/*.parquet"
+    - "mobile/understanding/validation/*/*.parquet"
+---
+
+# cua-lite/GUIOdyssey
+
+cua-lite preprocessed version of GUIOdyssey (hflqf88888/GUIOdyssey). A long-horizon cross-app Android mobile dataset of 8,334 task trajectories over ~128k screenshots. Produces two cohorts: navigation (multi-step agent episodes) and understanding (per-step screen captioning from the source `description` annotations).
+
+## Origin
+
+- [https://huggingface.co/datasets/hflqf88888/GUIOdyssey](https://huggingface.co/datasets/hflqf88888/GUIOdyssey)
+
+## Load via `datasets`
+
+```python
+from datasets import load_dataset
+
+# entire dataset
+ds = load_dataset("cua-lite/GUIOdyssey")
+
+# just one (platform, task_type) cohort
+ds = load_dataset("cua-lite/GUIOdyssey", "mobile.navigation")
+```
+
+You can also filter by `metadata.platform` / `metadata.task_type` /
+`metadata.others.*` after loading; every row carries a rich `metadata`
+struct (see schema below).
+
+## Schema
+
+Each row has these columns:
+
+| column | type | notes |
+|---|---|---|
+| `images` | list[Image] | embedded PNG/JPEG bytes; HF viewer renders thumbnails |
+| `messages` | list[struct] | OpenAI-style turns with `role` + structured `content` |
+| `metadata` | struct | `{platform, task_type, extra_tools, valid_actions, others{...}}` |
+
+Coordinate values in `messages` are normalized to `[0, 1000]` integers.
+
+**Image-dedup (`grounding.*` / `understanding` cohorts).** These cohorts are
+single-image-per-row and many rows share the same screenshot, so to avoid
+re-embedding identical image bytes once per instruction they are stored
+*folded*: one row per unique screenshot (image embedded once), carrying an
+extra **`_folded`** column — a JSON string with the authoritative list of
+`{messages, metadata}` members for that screenshot. The row's top-level
+`messages` is the members concatenated for viewer convenience. `navigation`
+cohorts are not folded. **Use `lite.data.hf.download` to consume this repo** —
+it unfolds automatically back to one row per instruction; reading the parquet
+directly yields the folded form.
+
+## Layout
+
+```
+<platform>/<task_type>/<split>/shard-NNNNN-of-NNNNN.parquet                  # single-variant cohort
+<platform>/<task_type>/<split>/<variant>/shard-NNNNN-of-NNNNN.parquet        # multi-variant cohort
+```
+
+- `platform` ∈ {desktop, mobile, web}
+- `task_type` ∈ {understanding, grounding.action, grounding.point, grounding.bbox, navigation} — used verbatim as the dir component
+- HF config names are `<platform>.<task_type>` (e.g. `mobile.grounding.action`). The agent registry lookup key in code is `<agent>@<platform>@<task_type>` (e.g. `qwen3_vl@mobile@grounding.action`); only this user-facing token uses `.` between platform and task_type, because `@` triggers a 403 on the dataset-viewer's signed image URLs.
+- HF split names stay `train` / `validation` (the `datasets` library blacklists `<>:/\|?*` in split names; everything else is fine in config_name)
+- `validation` is an in-distribution held-out slice (never used in training); `test` is reserved for out-of-distribution benchmark datasets
+
+## Stats
+
+| platform | task_type | variant | train | validation |
+|---|---|---|---:|---:|
+| mobile | navigation | navigation | 8,146 | 184 |
+| mobile | understanding | understanding | 125,893 | 2,000 |
+
+## Local mirror & SFT export
+
+For local workflows (SFT export, dedup, mixing across datasets), use
+`lite.data.hf.download` to mirror this repo back to the canonical local
+layout:
+
+```
+$CUA_LITE_DATASETS_ROOT/cua-lite/GUIOdyssey/
+  images/<hash[:2]>/<hash>.<ext>                          # content-addressed image store
+  <platform>/<task_type>/<split>[/<variant>].parquet      # rows reference images by relative path
+```
+
+Rows in the local parquet have `images: list[str]`; bytes are extracted to
+the image store. `lite.train.utils.data.export_sft` consumes the local
+form directly with `--image-root=$CUA_LITE_DATASETS_ROOT`.
+
+- Total unique images: **125,131**
+- Image store size: **92.16 GB**
+
+## Notes
+
+Source `info` coordinates are already normalized to [0, 1000] (per the upstream README) and are used directly — they are NOT device pixels.
+
+## License & citation
+
+See original dataset (hflqf88888/GUIOdyssey).
+
+See https://huggingface.co/datasets/hflqf88888/GUIOdyssey

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