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pretty_name: TutorGeo
language:
- en
task_categories:
- image-to-text
- visual-question-answering
tags:
- geometry
- mathematics
- multimodal
- instruction-tuning
size_categories:
- 100K<n<1M
configs:
- config_name: img2meta
data_files:
- split: train
path: img2meta/data.jsonl
- config_name: reasoning_multimodal_mathcanvas
data_files:
- split: train
path: reasoning/multimodal_reasoning/MathCanvasInstruct/data.jsonl
- config_name: reasoning_multimodal_mathvr
data_files:
- split: train
path: reasoning/multimodal_reasoning/MathVRTrain/data.jsonl
- config_name: reasoning_multimodal_zkpg
data_files:
- split: train
path: reasoning/multimodal_reasoning/ZKPG/data.jsonl
- config_name: reasoning_text_only_mathcanvas
data_files:
- split: train
path: reasoning/text_only_reasoning/MathCanvasInstruct/data.jsonl
- config_name: reasoning_text_only_mathvr
data_files:
- split: train
path: reasoning/text_only_reasoning/MathVRTrain/data.jsonl
- config_name: reasoning_text_only_zkpg
data_files:
- split: train
path: reasoning/text_only_reasoning/ZKPG/data.jsonl
---
# TutorGeo
TutorGeo contains image-to-meta conversion data and geometry-reasoning conversations used by MetaReason. All files use JSON Lines, with image paths relative to the TutorGeo directory.
Images are stored in seven tar files under `image_archives/`. Download and extract them from the TutorGeo root before using the JSONL files:
```bash
hf download pH202411/TutorGeo --repo-type dataset --local-dir TutorGeo
cd TutorGeo
for archive in image_archives/*.tar; do tar -xf "$archive"; done
```
The archives preserve the original directory structure, so the relative paths in each record's `images` field work after extraction.
## Contents
| Configuration | Examples |
| --- | ---: |
| `img2meta` | 27,695 |
| `reasoning_multimodal_mathcanvas` | 31,408 |
| `reasoning_multimodal_mathvr` | 21,317 |
| `reasoning_multimodal_zkpg` | 6,945 |
| `reasoning_text_only_mathcanvas` | 34,583 |
| `reasoning_text_only_mathvr` | 23,360 |
| `reasoning_text_only_zkpg` | 7,733 |
| **Total** | **153,041** |
Each line has the following structure:
```json
{
"messages": [
{"role": "user", "content": "..."},
{"role": "assistant", "content": "..."}
],
"images": ["img2meta/orig_images/example.png"]
}
```
## Load
From the Hugging Face Hub:
```python
from datasets import load_dataset
dataset = load_dataset("pH202411/TutorGeo", "img2meta", split="train")
```
From local files:
```python
from datasets import load_dataset
dataset = load_dataset(
"json",
data_files="img2meta/data.jsonl",
split="train",
)
```
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