Update README.md

README.md

@@ -27,7 +27,22 @@ RougeL= 23.499
 
 More information needed
 
-## Training and evaluation data
+To use its API:
+from transformers import BertTokenizerFast, GPT2Tokenizer, EncoderDecoderModel
+
+model = EncoderDecoderModel.from_pretrained("Ayham/roberta_gpt2_summarization_cnn_dailymail")
+# reuse tokenizer from bert2bert encoder-decoder model
+input_tokenizer = BertTokenizerFast.from_pretrained('bert-base-cased')
+
+
+article = """Your Input Text"""
+
+input_ids = input_tokenizer(article, return_tensors="pt").input_ids
+output_ids = model.generate(input_ids)
+
+# we need a gpt2 tokenizer for the output word embeddings
+output_tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
+print(output_tokenizer.decode(output_ids[0], skip_special_tokens=True))
 
 More information needed