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pH202411/TutorGeo

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: hf download pH202411/TutorGeo --repo-type dataset --local-dir TutorGeo cd TutorGeo for archive in image_archives/*.tar; do tar -xf "$archive"; done… See the full description on the dataset page: https://huggingface.co/datasets/pH202411/TutorGeo.

sourceHugging Faceupdated 1mo agoView on Hugging Face
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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

ConfigurationExamples
img2meta27,695
reasoning_multimodal_mathcanvas31,408
reasoning_multimodal_mathvr21,317
reasoning_multimodal_zkpg6,945
reasoning_text_only_mathcanvas34,583
reasoning_text_only_mathvr23,360
reasoning_text_only_zkpg7,733
Total153,041

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",
)