Add model card for GlyphPrinter

README.md

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+---
+pipeline_tag: text-to-image
+library_name: diffusers
+---
+
+# GlyphPrinter: Region-Grouped Direct Preference Optimization for Glyph-Accurate Visual Text Rendering
+
+[Paper](https://huggingface.co/papers/2603.15616) | [Project Page](https://henghuiding.com/GlyphPrinter/) | [GitHub](https://github.com/FudanCVL/GlyphPrinter)
+
+**GlyphPrinter** is a preference-based text rendering framework designed to eliminate the reliance on explicit reward models for visual text generation. It addresses common failure cases in existing text-to-image models, such as stroke distortions and incorrect glyphs, especially when rendering complex Chinese characters, multilingual text, or out-of-domain symbols.
+
+## Key Features
+
+- **R-GDPO (Region-Grouped Direct Preference Optimization):** A region-based objective that optimizes inter- and intra-sample preferences over annotated regions, substantially enhancing glyph accuracy.
+- **GlyphCorrector Dataset:** A specialized dataset with region-level glyph preference annotations.
+- **Regional Reward Guidance (RRG):** An inference strategy that samples from an optimal distribution with controllable glyph accuracy.
+
+## Usage
+
+To use this model, please follow the installation instructions in the [official GitHub repository](https://github.com/FudanCVL/GlyphPrinter).
+
+### CLI Inference
+
+You can run inference using the provided `inference.py` script:
+
+```bash
+# list available saved conditions
+python3 inference.py --list-conditions
+
+# run inference using a prompt
+python3 inference.py \
+  --prompt "The colorful graffiti font <sks1> printed on the street wall" \
+  --save-mask
+
+# run inference using a specific condition file
+python3 inference.py \
+  --condition condition_1.npz \
+  --output-dir outputs_inference
+```
+
+### Gradio Demo
+
+Alternatively, you can run the interactive Gradio app:
+```bash
+python app.py
+```
+
+## Citation
+```bibtex
+@inproceedings{GlyphPrinter,
+        title={{GlyphPrinter}: Region-Grouped Direct Preference Optimization for Glyph-Accurate Visual Text Rendering},
+        author={Shuai, Xincheng and Li, Ziye and Ding, Henghui and Tao, Dacheng},
+        booktitle={CVPR},
+        year={2026}
+      }
+```