Update README.md

README.md

@@ -18,5 +18,17 @@ def get_global_attention(input_ids):
     global_attention_mask.index_put_(tuple(globs.t()), value)
     return global_attention_mask
     
-   
+m1 = "In this paper we present the results of an experiment in <m> automatic concept and definition extraction </m> from written sources of law using relatively simple natural methods."
+m2 = "This task is important since many natural language processing (NLP) problems, such as <m> information extraction </m>, summarization and dialogue."
+
+inputs = m1 + " </s></s> " + m2  
+
+tokens = tokenzier(inputs, return_tensors='pt')
+global_attention_mask = get_global_attention(tokens['input_ids'])
+
+with torch.no_grad():
+    output = model(tokens['input_ids'], tokens['attention_mask'], global_attention_mask)
+    
+scores = torch.softmax(output.logits, dim=-1)
+
 ```