README.md

---
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: web-trajectory
  data_files:
  - split: train
    path:
    - "web/trajectory/train*parquet"
    - "web/trajectory/train/*.parquet"
    - "web/trajectory/train/*/*.parquet"
  - split: validation
    path:
    - "web/trajectory/validation*parquet"
    - "web/trajectory/validation/*.parquet"
    - "web/trajectory/validation/*/*.parquet"
---

# cua-lite/Multimodal-Mind2Web

cua-lite preprocessed version of Multimodal-Mind2Web (osunlp/Multimodal-Mind2Web). Web trajectory data with upstream's canonical four-way split: train + three held-out test sets (test_task, test_website, test_domain) capturing successively harder generalization. The upstream split labels are preserved via metadata.others.split and routed into our validation split; the hash splitter never activates here.

## Origin

- [https://huggingface.co/datasets/osunlp/Multimodal-Mind2Web](https://huggingface.co/datasets/osunlp/Multimodal-Mind2Web)

## Load via `datasets`

```python
from datasets import load_dataset

# entire dataset
ds = load_dataset("cua-lite/Multimodal-Mind2Web")

# just one (platform, task_type) cohort
ds = load_dataset("cua-lite/Multimodal-Mind2Web", "web-trajectory")
```

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 |
|---|---|---|
| `image_ids` | list[string] | content-addressed ids (`<sha256>.<ext>`), enables cross-parquet / cross-dataset dedup |
| `images` | list[Image] | bytes embedded at HF push time; matches `image_ids` index-for-index |
| `messages` | list[struct] | OpenAI-style turns with `role` + structured `content` |
| `metadata` | struct | `{platform, task_type, split, others{...}}` |

Coordinate values in `messages` are normalized to `[0, 1000]` integers.

## Layout

```
<platform>/<task_type>/<split>.parquet                   # single-variant cohort
<platform>/<task_type>/<split>/<variant>.parquet         # multi-variant cohort
<platform>/<task_type>/<split>/shard-NNNNN-of-NNNNN.parquet            # + sharded single-variant
<platform>/<task_type>/<split>/<variant>/shard-NNNNN-of-NNNNN.parquet  # + sharded multi-variant
```

- `platform` ∈ {desktop, mobile, web}
- `task_type` directory uses a hyphen where the metadata value uses a colon: `grounding-action/` → `grounding:action`
- `split` ∈ {train, validation} — `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 |
|---|---|---|---:|---:|
| web | trajectory | test_domain | 0 | 478 |
| web | trajectory | test_task | 0 | 99 |
| web | trajectory | test_website | 0 | 83 |
| web | trajectory | train | 602 | 0 |

## Image storage

Images are content-addressed by SHA-256 and deduplicated within this repo.
The `images` column on HuggingFace embeds raw bytes so the Hub viewer
renders thumbnails and `datasets.load_dataset` works out of the box.

For local workflows (SFT export, cross-dataset dedup, split rebalancing),
run [`reverse.py`](https://github.com/cua-lite/cua-lite/tree/main/scripts/hf_upload)
on a cloned repo: it extracts each unique `image_id` once to a shared
`image_store/<hash[:2]>/<hash>.<ext>` and rewrites the parquets to drop
the `images` column, so rows reference images by hash id only.  The shared
store is reusable across datasets — the same image in two repos lands in
one file.

- Total unique images: **7,423**
- Store size: **7.09 GB**

## Notes

All three test splits are currently folded into our ``validation`` split. A future revision may promote test_website / test_domain to our canonical ``test`` split (out-of-distribution benchmark).

## License & citation

See original dataset (osunlp/Multimodal-Mind2Web)

See https://huggingface.co/datasets/osunlp/Multimodal-Mind2Web