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README.md
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license: mit
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# Vector Graphics Generation
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This model generates vector graphics (SVG) from text prompts.
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## Usage
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- "a red sports car"
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- "a portrait of a woman"
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- "a cat playing with a ball"
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license: mit
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# DiffSketcher - Vector Graphics Generation
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This model generates vector graphics (SVG) from text prompts using the original DiffSketcher implementation.
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## Model Description
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DiffSketcher is a state-of-the-art vector graphics generation model that creates high-quality SVG images from text prompts. It uses a diffusion model to guide the SVG generation process.
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## Usage
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- "a red sports car"
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- "a portrait of a woman"
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- "a cat playing with a ball"
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## How It Works
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1. **Text Encoding**: The text prompt is encoded using CLIP.
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2. **Diffusion Process**: A diffusion model generates a latent representation.
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3. **SVG Generation**: The latent representation is used to generate an SVG.
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4. **PNG Conversion**: The SVG is converted to PNG for display.
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## Performance Considerations
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- The original implementation requires significant computational resources
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- Generation can take several minutes depending on the complexity
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- GPU acceleration is recommended for optimal performance
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