joanrod/star-vector

Health v2 · maintenance only

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4560 stars · 258 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

StarVector is a foundation model that generates scalable vector graphics (SVG) code from images and text by treating vectorization as a code generation task with a vision-language architecture. It ships pretrained 1B and 8B models on HuggingFace plus the SVG-Stack dataset and SVG-Bench benchmark.

Use cases

• convert raster images to svg code
• vectorize a png into scalable vector graphics
• generate svg icons from text descriptions
• image to svg code generation with a vision-language model
• benchmark svg generation models on svg-bench
• finetune a model for image-to-vector code generation

When to choose

• you need high-fidelity image-to-SVG conversion with editable vector output
• you want a pretrained multimodal model for SVG code generation
• you need a research baseline or benchmark for SVG generation

When to avoid

• you need simple one-off raster-to-vector tracing without GPU inference
• you lack GPU resources for large vision-language model inference
• you need production-grade vectorization of complex photographs

Facets

library · maturity active

machine-learning deep-learning image-processing llm-inference graphics artificial-intelligence machine-learning computer-vision graphics large-language-models python svg-generation vision-language-model image-to-code vectorization multimodal foundation-model gpu

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