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Update README.md

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@@ -37,14 +37,14 @@ You can use the `transformers` library to load and utilize the T5-Reverse (T5R)
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  ```python
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  # Import required libraries
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- import torch
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- from transformers import pipeline
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  # Load the model and tokenizer using the pipeline from Hugging Face Hub
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- inference = pipeline("text2text-generation", model="kargaranamir/T5R-base")
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  # Example instruction and prompt
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- sample = '''
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  Instruction: X
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  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.
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  What kind of instruction could this be the answer to?
@@ -52,9 +52,9 @@ X:
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  '''
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  # Generate a response using the model
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- res = inference(sample)
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  # Print the generated response
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- print(res)
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- >> [{'generated_text': 'Instruction: Generate three recommendations for a healthy diet.'}]
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  ```
 
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  ```python
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  # Import required libraries
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+ >>> import torch
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+ >>> from transformers import pipeline
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  # Load the model and tokenizer using the pipeline from Hugging Face Hub
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+ >>> inference = pipeline("text2text-generation", model="kargaranamir/T5R-base")
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  # Example instruction and prompt
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+ >>> sample = '''
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  Instruction: X
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  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.
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  What kind of instruction could this be the answer to?
 
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  '''
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  # Generate a response using the model
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+ >>> res = inference(sample)
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  # Print the generated response
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+ >>> print(res)
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+ [{'generated_text': 'Instruction: Generate three recommendations for a healthy diet.'}]
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  ```