| --- |
| dataset_info: |
| features: |
| - name: id |
| dtype: string |
| - name: images |
| list: |
| image: |
| mode: RGB |
| - name: state |
| dtype: json |
| - name: question |
| dtype: json |
| - name: label |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 2345294519 |
| num_examples: 4574 |
| - name: validation |
| num_bytes: 265093929 |
| num_examples: 512 |
| - name: test_task |
| num_bytes: 431600231 |
| num_examples: 833 |
| - name: test_website |
| num_bytes: 306363797 |
| num_examples: 634 |
| - name: test_domain |
| num_bytes: 1268157465 |
| num_examples: 2690 |
| download_size: 4593730999 |
| dataset_size: 4616509941 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| - split: validation |
| path: data/validation-* |
| - split: test_task |
| path: data/test_task-* |
| - split: test_website |
| path: data/test_website-* |
| - split: test_domain |
| path: data/test_domain-* |
| --- |
| |
| # Mind2Web decisions |
|
|
| Screenshot-based next-element decisions for fine-tuning Liquid d1. |
|
|
| This dataset accompanies the [code](https://github.com/DrChrisLevy/finetune-liquid-image-decisions) and [blog post](https://drchrislevy.com/blog/liquid-image-decisions) on fine-tuning Liquid image decision models. |
|
|
| ## Dataset format |
|
|
| ```python |
| Features({ |
| "id": Value("string"), |
| "images": List(Image(mode="RGB")), |
| "state": Json(), |
| "question": Json(), |
| "label": Value("string"), |
| }) |
| ``` |
|
|
| Abbreviated example (`image` is a decoded PIL image): |
|
|
| ```python |
| { |
| "id": "bf94a193-a30b-45b7-a93e-4733ea6a7ed4:b88c28d6-7d12-42fc-95b3-f4267b4fd200", |
| "images": [image], |
| "state": { |
| "task_and_past_actions": "Find an Alaska cruise in September 2023. Dates menu opened.", |
| "screenshot_size_pixels": [1280, 2343], |
| }, |
| "question": { |
| "type": "choice", |
| "instructions": "Select the next element to interact with.", |
| "criteria": { |
| "element_9": '{"aria_label": "October 2024", "bbox": [568, 926, 66, 50]}', |
| "element_17": '{"aria_label": "September 2023", "bbox": [208, 926, 66, 50]}', |
| }, |
| }, |
| "label": "element_17", |
| } |
| ``` |
|
|
| ## Load an example |
|
|
| Use streaming to read examples on demand without downloading the whole dataset: |
|
|
| ```python |
| from datasets import load_dataset |
| |
| dataset = load_dataset( |
| "chrislevy/mind2web-decisions", |
| split="train", |
| streaming=True, |
| ) |
| row = next(iter(dataset)) |
| row["images"][0] # PIL image |
| ``` |
|
|
| ## Source and normalization |
|
|
| Adapted from [tasksource/multimodal-mind2web](https://huggingface.co/datasets/tasksource/multimodal-mind2web), based on [Multimodal-Mind2Web](https://huggingface.co/datasets/osunlp/Multimodal-Mind2Web). The target is the correct next element. Screenshots are capped at 1 megapixel; bounding boxes use `[left, top, width, height]` in original-image pixels. Validation is held out by trajectory; official test splits are preserved. |
|
|
