Update README.md

README.md

@@ -36,14 +36,14 @@ This model is an instruction-tuned version of [google/flan-t5-base](https://hugg
 You can use the `transformers` library to load and utilize the T5-Reverse (T5R) model for generating prompts based on text. Here's an example of how to do it:
 
 ```python
-# Import required libraries
+>>> # Import required libraries
 >>> import torch
 >>> from transformers import pipeline
 
-# Load the model and tokenizer using the pipeline from Hugging Face Hub
+>>> # Load the model and tokenizer using the pipeline from Hugging Face Hub
 >>> inference = pipeline("text2text-generation", model="kargaranamir/T5R-base")
 
-# Example instruction and prompt
+>>> # Example instruction and prompt
 >>> sample = '''
 Instruction: X
 Output: 1- Base your meals on higher fibre starchy carbohydrates. 2- Eat lots of fruit and veg. 3- Eat more fish, including a portion of oily fish.
@@ -51,10 +51,11 @@ What kind of instruction could this be the answer to?
 X:
 '''
 
-# Generate a response using the model
+>>> # Generate a response using the model
 >>> res = inference(sample)
 
-# Print the generated response
+>>> # Print the generated response
 >>> print(res)
+
 [{'generated_text': 'Instruction: Generate three recommendations for a healthy diet.'}]
 ```