Update README.md

README.md

@@ -88,14 +88,15 @@ More information needed
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
 # Load model and tokenizer
-model_name = "username/model-name"
-model = AutoModelForCausalLM.from_pretrained(model_name)
+model_name = "psxjp5/mt5-small"
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 
 # Generate text
-input_text = "Once upon a time"
-input_ids = tokenizer.encode(input_text, return_tensors="pt")
-output = model.generate(input_ids, max_length=50)
+context = "Once upon a time"
+question = "What is time"
+input_ids = tokenizer(context, question, return_tensors="pt").input_ids
+outputs = model.generate(input_ids, max_new_tokens=150)
 
 print(tokenizer.decode(output[0], skip_special_tokens=True))
 ```