Update README.md

model_cards/microsoft/xprophetnet-large-wiki100-cased/README.md

+---
+language: multilingual
+---
+
 ## xprophetnet-large-wiki100-cased
 Cross-lingual version [ProphetNet](https://arxiv.org/abs/2001.04063), pretrained on [wiki100 xGLUE dataset](https://arxiv.org/abs/2004.01401).  
 ProphetNet is a new pre-trained language model for sequence-to-sequence learning with a novel self-supervised objective called future n-gram prediction.  
@@ -5,8 +9,27 @@ ProphetNet is able to predict more future tokens with a n-stream decoder. The or
 
 xProphetNet is also served as the baseline model for xGLUE cross-lingual natural language generation tasks.  
 For xGLUE corss-lingual NLG tasks, xProphetNet is finetuned with English data, but inference with both English and other zero-shot language data. 
+
 ### Usage
-Please see [the official repository](https://github.com/microsoft/ProphetNet/tree/master/xProphetNet) for details.
+
+This pre-trained model can be fine-tuned on *sequence-to-sequence* tasks. The model could *e.g.* be trained on English headline generation as follows:
+
+```python 
+from transformers import XLMProphetNetForConditionalGeneration, XLMProphetNetTokenizer
+
+model = XLMProphetNetForConditionalGeneration.from_pretrained("microsoft/xprophetnet-large-wiki100-cased")
+tokenizer = XLMProphetNetTokenizer.from_pretrained("microsoft/xprophetnet-large-wiki100-cased")
+
+input_str = "the us state department said wednesday it had received no formal word from bolivia that it was expelling the us ambassador there but said the charges made against him are `` baseless ."
+target_str = "us rejects charges against its ambassador in bolivia"
+
+input_ids = tokenizer(input_str, return_tensors="pt").input_ids
+labels = tokenizer(target_str, return_tensors="pt").input_ids
+
+loss = model(input_ids, labels=labels, return_dict=True).loss
+```
+
+Note that since this model is a multi-lingual model it can be fine-tuned on all kinds of other languages.
 
 ### Citation
 ```bibtex