Update README.md

README.md

@@ -54,12 +54,21 @@ The usage is straightforward and very similar to any other instruction fine-tune
 
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer
+
 checkpoint_name="ArmelR/starcoder-gradio-v0"
 model = AutoModelForCausalLM.from_pretrained(checkpoint_name)
 tokenizer = AutoTokenizer.from_pretrained(checkpoint_name)
+
 prompt = "Create a gradio application that help to convert temperature in celcius into temperature in Fahrenheit"
 inputs = tokenizer(f"Question: {prompt}\n\nAnswer: ", return_tensors="pt")
-outputs = model.generate(inputs["input_ids"], temperature=0.2, top_p=0.95, max_length=200)
+
+outputs = model.generate(
+  inputs["input_ids"],
+  temperature=0.2,
+  top_p=0.95,
+  max_new_tokens=200
+)
+
 input_len=len(inputs["input_ids"])
 print(tokenizer.decode(outputs[0][input_len:]))
 ```