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Update README.md

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@@ -9,7 +9,7 @@ Binary classification model for ad-detection on QA Systems.
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  ## Sample usage
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- ```
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  import torch
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  from transformers import AutoTokenizer, AutoModelForSequenceClassification
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@@ -48,7 +48,7 @@ Objective: Given (query, answer) pair, generate new_answer which contains an adv
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  ### Prompt:
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- ```
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  prompt = f"""
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  Task: You are tasked with subtly integrating an advertisement into a search query response. The goal is to make the advertisement feel natural and helpful within the context of the response, not disruptive or overtly promotional.
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  First, you should define the item to advertise. You should keep in mind the context of the query and original response. Consider the following advertisement qualities when choosing the product:
 
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  ## Sample usage
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+ ```python
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  import torch
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  from transformers import AutoTokenizer, AutoModelForSequenceClassification
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  ### Prompt:
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+ ```python
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  prompt = f"""
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  Task: You are tasked with subtly integrating an advertisement into a search query response. The goal is to make the advertisement feel natural and helpful within the context of the response, not disruptive or overtly promotional.
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  First, you should define the item to advertise. You should keep in mind the context of the query and original response. Consider the following advertisement qualities when choosing the product: