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README.md

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+---
+license: apache-2.0
+---
+# CogView2
+## Model description
+
+**CogView2: Faster and Better Text-to-Image Generation via Hierarchical Transformers**
+
+- [Paper](https://arxiv.org/abs/2204.14217)
+- [GitHub Repo](https://github.com/THUDM/CogView2)
+
+### Abstract
+
+The development of the transformer-based text-to-image models are impeded by its slow generation and complexity for high-resolution images. In this work, we put forward a solution based on hierarchical transformers and local parallel auto-regressive generation. We pretrain a 6B-parameter transformer with a simple and flexible self-supervised task, Cross-modal general language model (CogLM), and finetune it for fast super-resolution. The new text-to-image system, CogView2, shows very competitive generation compared to concurrent state-of-the-art DALL-E-2, and naturally supports interactive text-guided editing on images.
+
+## BibTeX entry and citation info
+```bibtex
+@article{ding2022cogview2,
+  title={CogView2: Faster and Better Text-to-Image Generation via Hierarchical Transformers},
+  author={Ding, Ming and Zheng, Wendi and Hong, Wenyi and Tang, Jie},
+  journal={arXiv preprint arXiv:2204.14217},
+  year={2022}
+}
+```