| --- |
| task_categories: |
| - image-text-to-text |
| tags: |
| - chart-to-code |
| - code-generation |
| - multimodal |
| pretty_name: VinciCoder Chart2Code 0-10k (seed 0) |
| --- |
| |
| # VinciCoder Chart2Code, rows 0-10000 of seed 0 |
|
|
| 10,000 chart-to-code examples (chart image, instruction, reference matplotlib program) drawn from |
| the `chart2code_1.parquet` file of [DocTron-Hub/VinciCoder-1.6M-SFT](https://huggingface.co/datasets/DocTron-Hub/VinciCoder-1.6M-SFT) |
| (revision `974a038fb6f695e7a935112d4df430926fc468b3`). All rights and terms are those of the source dataset and the works it collects. |
|
|
| ## Selection |
|
|
| - The first 163,186 of the file's 210,137 rows (the Chart2Code head) are split by SHA-256 of the image: |
| 1% held out (1,678 rows, never included here), 161,508 for training. |
| - The training rows are shuffled once with `random.Random(0).shuffle(train_indices)`; this dataset is |
| positions `[0, 10000)` of that order, in that order. `permutation.json` holds the full order |
| (sha256 `bc4a30fffc10377e4c56b71dfbe5679a5e93e5d3723a392c4d7abcc3cc90aa34`), so `[10000, 10000 + N)` gives the next, non-overlapping chunk. |
| - `manifest.json` records the source split and the sha256 of these indices (`f399c46e442a9895af38ed8c7e74a3d884f5059980c2a486f9a4d8ec3c32c8ff`). |
|
|
| ## Columns |
|
|
| | Column | Meaning | |
| |---|---| |
| | `source_index` | Row number in the source `chart2code_1.parquet` | |
| | `image` | Reference chart | |
| | `user_content` | Instruction | |
| | `assistant_content` | Reference answer (matplotlib code) | |
|
|
