Update README.md

README.md

@@ -1,8 +1,47 @@
 ---
 library_name: paddlenlp
+license: apache-2.0
 tags:
 - summarization
 language:
 - zh
 ---
-# PaddlePaddle/unimo-text-1.0-summary
+
+[![paddlenlp-banner](https://user-images.githubusercontent.com/1371212/175816733-8ec25eb0-9af3-4380-9218-27c154518258.png)](https://github.com/PaddlePaddle/PaddleNLP)
+
+# PaddlePaddle/unimo-text-1.0-summary
+
+## Introduction
+
+Existed pre-training methods either focus on single-modal tasks or multi-modal tasks, and cannot effectively adapt to each other. 
+They can only utilize single-modal data (i.e. text or image) or limited multi-modal data (i.e. image-text pairs). 
+In this work, we propose a unified-modal pre-training architecture, namely UNIMO, which can effectively adapt to both single-modal and multi-modal 
+understanding and generation tasks. Large scale of free text corpus and image collections can be utilized to improve the capability of visual 
+and textual understanding, and cross-modal contrastive learning (CMCL) is leveraged to align the textual and visual information into a unified 
+semantic space over a corpus of image-text pairs. As the non-paired single-modal data is very rich, our model can utilize much larger scale of 
+data to learn more generalizable representations. Moreover, the textual knowledge and visual knowledge can enhance each other in the unified semantic space. 
+The experimental results show that UNIMO significantly improves the performance of several single-modal and multi-modal downstream tasks.
+
+More detail: https://arxiv.org/abs/2012.15409
+
+## Available Models
+
+- unimo-text-1.0
+- unimo-text-1.0-large
+- unimo-text-1.0-summary
+
+## How to Use?
+
+Click on the *Use in paddlenlp* button on the top right!
+
+## Citation Info
+
+```text
+@article{ernie2.0,
+  title = {UNIMO: Towards Unified-Modal Understanding and Generation via Cross-Modal Contrastive Learning},
+  author = {Li, Wei and Gao, Can and Niu, Guocheng and Xiao, Xinyan and Liu, Hao and Liu, Jiachen and Wu, Hua and Wang, Haifeng},
+  journal={arXiv preprint arXiv:2012.15409},
+  year = {2020},
+}
+```
+