metadata
license: cc-by-nc-4.0
language:
- en
base_model:
- deepseek-ai/deepseek-coder-6.7b-instruct
- google/siglip-so400m-patch14-384
pipeline_tag: image-text-to-text
Aligned Multi-View Scripts for Universal Chart-to-Code Generation
CharLuMA-1.3B generates a plotting script in Python, R, or LaTeX from a chart image. This 1.3B variant is from the paper "Aligned Multi-View Scripts for Universal Chart-to-Code Generation" (ACL 2026 Main Conference).
- Paper: https://arxiv.org/abs/2604.24559
- Code (required for inference): https://github.com/zhihan72/CharLuMA
- 6.7B Variant: CharLuMA-6.7B
- Training data: Chart2NCode
| Backbone | Vision encoder | Output languages | dtype |
|---|---|---|---|
| DeepSeek-Coder-1.3B-Instruct | SigLIP-SO400M-patch14-384 | Python, R, LaTeX | bfloat16 |
Usage
This is a custom architecture, so AutoModel.from_pretrained will not load it.
Clone the codebase and use its loader:
git clone https://github.com/Zhihan72/CharLuMA
Before loading, replace the placeholder paths in config.json (/your_local_path/...) with deepseek-ai/deepseek-coder-1.3b-instruct (or a local copy) and google/siglip-so400m-patch14-384 (or a local copy).
Inference example: scripts/inference_charluma.py in the repo.
Citation
If you find our work useful, consider citing our paper as follows:
@misc{zhang2026aligned,
title = {Aligned Multi-View Scripts for Universal Chart-to-Code Generation},
author = {Zhihan Zhang and Lizi Liao},
year = {2026},
eprint = {2604.24559},
archivePrefix = {arXiv},
primaryClass = {cs.CL},
url = {https://arxiv.org/abs/2604.24559}
}