Update README.md

README.md

@@ -26,4 +26,23 @@ model_output = discord_qg.generate(**encoder_ids)
 
 generated_texts = dqg_tokenizer.batch_decode(model_output, skip_special_tokens=True)
 print(generated_texts) #  ['When was the last time the IMF warned of a global recession?']
-```
+```
+
+The model has a tendency to generate "When " questions. If you would rather generate other questions you can do the following:
+
+```py
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+qg_tokenizer = AutoTokenizer.from_pretrained("Salesforce/discord_qg")
+qg_model = AutoModelForSeq2SeqLM.from_pretrained("Salesforce/discord_qg")
+
+paragraph = "The International Monetary Fund warned on Tuesday that colliding pressures from inflation, war-driven energy and food crises and sharply higher interest rates were pushing the world to the brink of recession and threatening financial market stability."
+
+for start_word in ["How", "Why"]:
+    encoder_ids = qg_tokenizer.batch_encode_plus([paragraph], add_special_tokens=True, padding=True, truncation=True, return_tensors="pt")
+    decoder_input_ids = qg_tokenizer.batch_encode_plus([start_word], add_special_tokens=True, return_tensors="pt")["input_ids"][:, :-1]
+    model_output = qg_model.generate(**encoder_ids, decoder_input_ids=decoder_input_ids, max_length=20)
+    generated_questions = qg_tokenizer.batch_decode(model_output, skip_special_tokens=True)
+
+    print(generated_questions)
+ ```