Update README.md

README.md

@@ -1 +1,26 @@
-EconBERTa - RoBERTa further trained on 4GB of uncompressed text sourced from economics books
+EconBERTa - RoBERTa further trained on 4GB of uncompressed text sourced from economics books.
+
+Example usage for MLM: 
+
+from transformers import RobertaTokenizer, RobertaForMaskedLM
+from transformers import pipeline
+
+tokenizer = RobertaTokenizer.from_pretrained('roberta-base')
+model = RobertaForMaskedLM.from_pretrained('models').cpu()
+model.eval()
+mlm = pipeline('fill-mask', model = model, tokenizer  = tokenizer)
+test = "ECB - euro, FED - <mask>, BoJ - yen"
+print(mlm(test)[:2])
+
+Will give:
+
+[{'sequence': 'ECB - euro, FED - dollar, BoJ - yen',
+  'score': 0.7342271208763123,
+  'token': 1404,
+  'token_str': ' dollar'},
+ {'sequence': 'ECB - euro, FED - dollars, BoJ - yen',
+  'score': 0.10828445851802826,
+  'token': 1932,
+  'token_str': ' dollars'}]
+
+