Update README.md

README.md

@@ -1,4 +1,20 @@
-This model can convert the literal expression to figurative/metaphorical expression.
+This model can convert the literal expression to figurative/metaphorical expression. Below is the usage of our model:
+
+
+      from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+      
+      tokenizer = AutoTokenizer.from_pretrained("figurative-nlp/t5-figurative-generation")
+      model = AutoModelForSeq2SeqLM.from_pretrained("figurative-nlp/t5-figurative-generation")
+      
+      
+      input_ids = tokenizer(
+          "research is <m> very difficult </m> for me.", return_tensors="pt"
+      ).input_ids  # Batch size 1
+      outputs = model.generate(input_ids,beam_search = 5)
+      result = tokenizer.decode(outputs[0], skip_special_tokens=True)
+      #result : research is a tough nut to crack for me.
+
+
 
 For example (the &lt;m&gt; and &lt;/m&gt; is the mark that inform the model which literal expression we want to convert it as  figurative expression):