Qwen3-VL-2B-LaTeX-OCR

Qwen3-VL-2B-LaTeX-OCR

A 2B parameter vision-language model fine-tuned from Qwen/Qwen3-VL-2B-Instruct for LaTeX formula recognition from images. This model converts mathematical formula images into accurate LaTeX code.

Model Highlights

• Specialized for LaTeX OCR: Trained to accurately transcribe mathematical formulas from images to LaTeX
• Multi-Format Support: Handles inline formulas, display equations, matrices, and complex multi-line expressions
• High Accuracy: Significantly improved formula recognition over the base model
• Vision-Language Architecture: Leverages Qwen3-VL's visual understanding capabilities

Model Description

Training Data

Trained on the LaTeX-OCR dataset for mathematical formula image to LaTeX conversion. The dataset contains rendered LaTeX formulas paired with their source LaTeX code.

Data Composition

Quick Start

Using Transformers

from transformers import AutoModelForCausalLM, AutoProcessor
from PIL import Image

model_name = "Kassadin88/Qwen3-VL-2B-LaTeX-OCR"

model = AutoModelForCausalLM.from_pretrained(
    model_name,
    trust_remote_code=True,
    torch_dtype="auto"
)
processor = AutoProcessor.from_pretrained(
    model_name,
    trust_remote_code=True
)

image = Image.open("formula.png")
messages = [
    {"role": "user", "content": [
        {"type": "image"},
        {"type": "text", "text": "Transcribe the formula in the image to LaTeX."}
    ]}
]

inputs = processor.apply_chat_template(
    messages,
    images=[image],
    return_tensors="pt"
)
outputs = model.generate(**inputs, max_new_tokens=512)
result = processor.decode(outputs[0], skip_special_tokens=True)
print(result)

Using vLLM (Recommended for Production)

vllm serve Kassadin88/Qwen3-VL-2B-LaTeX-OCR \
    --port 8000 \
    --max-model-len 4096 \
    --trust-remote-code

Usage Tips

For Best Results

• Use high-resolution, clean images for best recognition accuracy
• Crop images tightly around the formula to reduce background noise
• For multi-page documents, process one formula at a time

Example Prompt

messages = [
    {"role": "user", "content": [
        {"type": "image"},
        {"type": "text", "text": "Convert this mathematical formula to LaTeX."}
    ]}
]

Limitations

• May struggle with handwritten formulas or low-quality images
• Complex multi-line derivations with mixed text and math may require manual review
• Not designed for general OCR tasks (text recognition from documents)
• Limited to mathematical notation; does not handle chemical equations or circuit diagrams

Citation

@misc{qwen3-vl-2b-latex-ocr,
    author = {Kassadin88},
    title = {Qwen3-VL-2B-LaTeX-OCR: A Fine-Tuned Vision-Language Model for LaTeX OCR},
    year = {2026},
    publisher = {HuggingFace},
    url = {https://huggingface.co/Kassadin88/Qwen3-VL-2B-LaTeX-OCR}
}

Acknowledgments

• Base Model: Qwen Team for Qwen3-VL
• Training Data: linxy for the LaTeX-OCR dataset

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Note: This model is intended for research and educational purposes. Please use responsibly.