Datasets:
| dataset_info: | |
| features: | |
| - name: images | |
| list: | |
| image: | |
| decode: false | |
| - name: image_group_id | |
| dtype: string | |
| - name: qa | |
| list: | |
| - name: inputs | |
| dtype: string | |
| - name: choices_list | |
| list: string | |
| - name: labels | |
| dtype: int64 | |
| - name: metadata | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 3782962890 | |
| num_examples: 94135 | |
| - name: validation | |
| num_bytes: 3792161 | |
| num_examples: 100 | |
| download_size: 3786274082 | |
| dataset_size: 3786755051 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| - split: validation | |
| path: data/validation-* | |
| language: | |
| - en | |
| license: | |
| - mit | |
| - cc-by-4.0 | |
| source_datasets: | |
| - maveryn/sphinx | |
| task_categories: | |
| - multiple-choice | |
| - visual-question-answering | |
| tags: | |
| - decision-model | |
| - procedural | |
| # sphinx-mcq | |
| Fresh SPHINX visual MC: charts, transformations and geometric counting. | |
| Uses four reviewed task families, native same-scene choices and nearby count | |
| alternatives. Original panel labels stay fixed in images. Gold comes from the | |
| native constructive generator and its uniqueness guards, not a model judge. | |
| Code is MIT; shipped icon assets carry CC BY 4.0 attribution. | |
| Original data: [maveryn/sphinx](https://huggingface.co/datasets/maveryn/sphinx), [original distribution](https://github.com/maveryn/sphinx). Repackaged as parquet for [tasksource](https://github.com/sileod/tasksource) by [scripts/repackage_dataset/procedural/suites.py](https://github.com/sileod/tasksource/blob/main/scripts/repackage_dataset/procedural/suites.py#L99). | |
| [Conversion provenance](provenance.json): source revisions, hashes, configuration and exclusions. | |
| [Upstream asset credits and licenses](asset-notices.json) accompany the original rendered images. | |
| [Generation checkpoints](generation-checkpoints.json) record each chunk’s seeds and exclusions. Reproduce with the [resumable scale script](https://github.com/sileod/tasksource/blob/main/scripts/repackage_dataset/procedural/scale.py). | |