[README] link to Write With Transformer

README.md

@@ -21,6 +21,7 @@ These implementations have been tested on several datasets (see the example scri
 | Section | Description |
 |-|-|
 | [Installation](#installation) | How to install the package |
+| [Online demo](#online-demo) | Experimenting with this repo’s text generation capabilities |
 | [Quick tour: Usage](#quick-tour) | Tokenizers & models usage: Bert and GPT-2 |
 | [Quick tour: Fine-tuning/usage scripts](#quick-tour-of-the-fine-tuningusage-scripts) | Using provided scripts: GLUE, SQuAD and Text generation |
 | [Migrating from pytorch-pretrained-bert to pytorch-transformers](#Migrating-from-pytorch-pretrained-bert-to-pytorch-transformers) | Migrating your code from pytorch-pretrained-bert to pytorch-transformers |
@@ -68,6 +69,14 @@ It contains an example of a conversion script from a Pytorch trained Transformer
 At some point in the future, you'll be able to seamlessly move from pre-training or fine-tuning models in PyTorch to productizing them in CoreML,
 or prototype a model or an app in CoreML then research its hyperparameters or architecture from PyTorch. Super exciting!
 
+## Online demo
+
+**[Write With Transformer](https://transformer.huggingface.co)**, built by the Hugging Face team at transformer.huggingface.co, is the official demo of this repo’s text generation capabilities.
+You can use it to experiment with completions generated by `GPT2Model`, `TransfoXLModel`, and `XLNetModel`.
+
+> “🦄 Write with transformer is to writing what calculators are to calculus.”
+
+![write_with_transformer](https://transformer.huggingface.co/assets/thumbnail-large.png)
 
 ## Quick tour