Datasets:
File size: 1,477 Bytes
16c5bab 70a5d14 16c5bab 70a5d14 ba1cbcc 70a5d14 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | ---
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) |
|