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Chartqwen
Sayeem26s/Chartqwen
Chartqwen is a image-to-text model from Sayeem26s. Use it when you need a caption or text from an image. It is set up for transformers. The card lists the license as apache-2.0.
ChartQwen is a vision-language model fine-tuned from Qwen/Qwen-VL for chart understanding tasks. The model is designed to interpret visual charts such as bar charts, line graphs, and plots, and answer natural language…
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Updated Jan 29, 2026
Repo size
392 MB
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At a glance
- Task
- Image-to-Text
- Library
- transformers
- License
- apache-2.0
- Access
- Public
- Created
- Jan 28, 2026
- Updated
- Jan 29, 2026
- SHA
- 339c0d22
Base models
Datasets
Model card
From the Hugging Face model README
ChartQwen
Model Description
ChartQwen is a vision-language model fine-tuned from Qwen/Qwen-VL for chart understanding tasks.
The model is designed to interpret visual charts such as bar charts, line graphs, and plots, and answer natural language questions related to them.
It supports multimodal reasoning by jointly processing images and text prompts.
Intended Use
This model can be used for:
- Chart question answering
- Chart data interpretation
- Visual reasoning over plots and graphs
- Document and report analysis involving charts
Training Details
- Base model: Qwen/Qwen-VL
- Modality: Image + Text
- Fine-tuning type: Supervised fine-tuning on chart-related visual-question pairs
- Dataset: Custom chart dataset (generated and curated for chart understanding)
Limitations
- Performance may degrade on low-resolution or highly cluttered charts
- The model may struggle with handwritten charts or uncommon chart styles
- Numerical precision depends on chart clarity
- Task
- Image-to-Text
- Library
- transformers
- License
- apache-2.0
- Languages
- en
- Created
- Jan 28, 2026
- Updated
- Jan 29, 2026