Update README.md

README.md

@@ -78,7 +78,7 @@ sampling_params = SamplingParams(
   max_tokens=8192,
 )
 llm = LLM(model="Unbabel/Tower-Plus-2B", tensor_parallel_size=1)
-messages = [{"role": "user", "content": "Translate: Hello, world! into Portuguese."}]
+messages = [{"role": "user", "content": "Translate the following English source text to Portuguese (Portugal):\nEnglish: Hello world!\nPortuguese (Portugal): "}]
 outputs = llm.chat(messages, sampling_params)
 # Make sure your prompt_token_ids look like this
 print (outputs[0].outputs[0].text)
@@ -96,7 +96,7 @@ from transformers import pipeline
 
 pipe = pipeline("text-generation", model="Unbabel/Tower-Plus-2B", device_map="auto")
 # We use the tokenizer’s chat template to format each message - see https://huggingface.co/docs/transformers/main/en/chat_templating
-messages = [{"role": "user", "content": "Translate: Hello, world! into Portuguese."}]
+messages = [{"role": "user", "content": "Translate the following English source text to Portuguese (Portugal):\nEnglish: Hello world!\nPortuguese (Portugal): "}]
 input_ids = pipe.tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True)
 outputs = pipe(messages, max_new_tokens=256, do_sample=False)
 print(outputs[0]["generated_text"])