cua-lite/Lite.ScaleCUA.wip

cua-lite/Lite.ScaleCUA.wip

TEMP resume coordination (raw; delete after merge)

Origin

Load via datasets

from datasets import load_dataset

# entire dataset
ds = load_dataset("cua-lite/Lite.ScaleCUA.wip")

# just one named subset (config)
ds = load_dataset("cua-lite/Lite.ScaleCUA.wip", "desktop.use.rl")

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:

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. use 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, use} — used verbatim as the dir component
• —HF config names are <platform>.<task_type> by default (e.g. mobile.grounding.action) — UNLESS the dataset was staged with --config-names, which sets verbatim, explicitly-chosen config names (see the configs: block above for the authoritative list). 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

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/Lite.ScaleCUA.wip/
  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.export.export_sft consumes the local form directly with --image-root=$CUA_LITE_DATASETS_ROOT.

• —Total unique images: 64,449
• —Image store size: 29.60 GB

Notes

Staged via lite.data.hf.stage from rollout log-roots: .data/rollout/lite.scalecua/gpt/5c3429d9/rl, .data/rollout/lite.scalecua/gpt/5c3429d9/train (row filter: none).

License & citation

other