Update app.py

app.py

@@ -13,6 +13,8 @@ model = GPT2LMHeadModel.from_pretrained("gpt2-large", pad_token_id=tokenizer.eos
 
 def generate(prompt,textCount):
     input_ids = tokenizer.encode(prompt, return_tensors='pt')
+    if textCount == None or textCount < 200:
+        textCount=200
     # generate text until the output length (which includes the context length) reaches 50
     output = model.generate(input_ids, max_length=textCount, num_beams=5, no_repeat_ngram_size=2, early_stopping=True)
     out = tokenizer.decode(output[0], skip_special_tokens=True)