| license: mit | |
| tags: | |
| - text-to-image | |
| - svg | |
| - vector-graphics | |
| pipeline_tag: text-to-image | |
| widget: | |
| - text: "a beautiful mountain landscape" | |
| example_title: "Mountain Landscape" | |
| - text: "a cute cat sitting on a windowsill" | |
| example_title: "Cat on Windowsill" | |
| - text: "a futuristic city skyline at sunset" | |
| example_title: "Futuristic City" | |
| # Vector Graphics Model | |
| This model generates vector graphics (SVG) from text prompts. | |
| ## Usage | |
| ```python | |
| import requests | |
| API_URL = "https://api-inference.huggingface.co/models/jree423/diffsketcher" | |
| headers = {"Authorization": "Bearer YOUR_API_TOKEN"} | |
| def query(payload): | |
| response = requests.post(API_URL, headers=headers, json=payload) | |
| return response.json() | |
| # Text-to-image input | |
| output = query({ | |
| "inputs": "a beautiful mountain landscape", | |
| }) | |
| # The response contains: | |
| # - svg: The SVG content as a string | |
| # - svg_base64: The SVG content encoded as base64 | |
| # - png_base64: A PNG version of the SVG encoded as base64 | |
| ``` | |
| ## Model Details | |
| This model generates vector graphics (SVG) from text prompts. It produces clean, scalable vector graphics that can be used in various applications. | |
| ## Limitations | |
| This is a placeholder implementation that returns simple SVG graphics. The full model implementation will be added in the future. |