---
license: cc-by-sa-4.0
task_categories:
- text-classification
- text-generation
tags:
- agent
- math
- Mathematics
- Large
- LLM
- large
- Math
- mathematics
- LATEX
- latex
- LaTeX
- good_quality
pretty_name: MathOCR
size_categories:
- 100M<n<1B
---

# Dataset Card for MathOCR

## Dataset Details

### Dataset Description

- **Curated by:** Roman
- **Funded by Roman:** [No funding needed]
- **Shared by Roman:** Also made by Roman
- **Language(s) (NLP):** English
- **License:** Common Creatives Attribution Share Alike 4.0

### Dataset Sources [optional]

- **Repository:** [https://huggingface.co/datasets/DataMuncher-Labs/LaTeXOCR]
- **I don't write papers or demos**

## Uses

<!-- Address questions around how the dataset is intended to be used. -->

### Direct Use

<!-- This section describes suitable use cases for the dataset. -->

[Pre/Post training corpra for visual understanding of mathematics.]

### Out-of-Scope Use

<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->

[Its not meant, but technically works for diffusion models.]
[The only way this dataset can be misused is in]
**A.** [Incompatible models, like TTS]
**B.** [Copying the repo without crediting mep

## Dataset Structure

<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->

[The dataset uses the format of]
problem_latex|solution_latex|problem_english


## Dataset Creation

### Curation Rationale

<!-- Motivation for the creation of this dataset. -->

[I thought there was simply a lack of mathematical OCR datasets]

### Source Data

<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->

#### Data Collection and Processing

<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->

[Data was sourced from python...]
**Its synthetic data**
<!--*I don't upload webscraped data cause im afraid i could get copyrighted ;-;*-->

#### Who are the source data producers?

<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->

[Roman]
[Ai assisted in making some parts of the script (sympy is hard)]

#### Personal and Sensitive Information

<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->

[No PII or Sensitive information]
*Also why I make synthtic data*

## Bias, Risks, and Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. -->

[Doesnt cover all equation types]
[Doesnt cover all numbers possible]
[There are aready similar datasets]

### Recommendations

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

**Just don't use it for the wrong models.**
*I know someone was thinking of giving this to a speech model...*

## Citation [optional]

<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**

@dataset{datamuncher_latexocr_2026,
  author       = {DataMuncher-Labs},
  title        = {LaTeXOCR},
  year         = {2026},
  publisher    = {Hugging Face},
  url          = {https://huggingface.co/datasets/DataMuncher-Labs/LaTeXOCR},
  note         = {Synthetic LaTeX equation OCR dataset}
}

**APA:**

**DataMuncher-Labs. (2026). LaTeXOCR [Dataset]. Hugging Face. https://huggingface.co/datasets/DataMuncher-Labs/LaTeXOCR**


## Dataset Card Authors

[Roman]

## Dataset Card Contact

[Email is **romanfinal@proton.me** please don't spam]
[Feel free to open a discussion on the repo]