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@@ -18,15 +18,31 @@ size_categories:
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  This is a subset of [sentence-transformers/gooaq](https://huggingface.co/datasets/sentence-transformers/gooaq).
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  This dataset is a collection of question-answer pairs, collected from Google. See GooAQ for additional information. This dataset can be used directly with Sentence Transformers to train embedding models.
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- Dataset Subsets
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- pair subset
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-
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- Columns: "question", "answer", "category"
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- Column types: str, str
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- Examples:
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-
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- {
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- 'question': 'is toprol xl the same as metoprolol?',
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- 'answer': 'Metoprolol succinate is also known by the brand name Toprol XL. It is the extended-release form of metoprolol. Metoprolol succinate is approved to treat high blood pressure, chronic chest pain, and congestive heart failure.',
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- 'category': 'Chemistry'
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- }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  This is a subset of [sentence-transformers/gooaq](https://huggingface.co/datasets/sentence-transformers/gooaq).
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  This dataset is a collection of question-answer pairs, collected from Google. See GooAQ for additional information. This dataset can be used directly with Sentence Transformers to train embedding models.
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+
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+ ## Dataset Subsets
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+
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+ Columns: "question", "answer", "category"
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+ Column types: str, str
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+ Examples:
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+
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+ {
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+ 'question': 'is toprol xl the same as metoprolol?',
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+ 'answer': 'Metoprolol succinate is also known by the brand name Toprol XL. It is the extended-release form of metoprolol. Metoprolol succinate is approved to treat high blood pressure, chronic chest pain, and congestive heart failure.',
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+ 'category': 'Chemistry'
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+ }
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+
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+ ## Method of categorization
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+
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+ Llama-3.1-8B was queried for category for each question using the following function:
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+ ```python
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+ def get_category(row):
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+ query = "You need to categorize the following question into one of the following categories: "
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+ categories = ["Biology", "Chemistry", "Physics", "Mathematics", "Computer Science", "Medicine", "Pop culture", "History", "Philosophy", "Art", "Music", "Sports", "Politics", "Religion", "Other"]
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+ query += ", ".join(categories)
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+ query += ". The question is: ```" + row["question"] + "```"
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+ query += ". The answer is: ```" + row["answer"] + "```"
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+ query += "\n Answer only with the category name, no other text."
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+ return ask_llm(query)
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+ ```
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+
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+ This subset consists only of the following categories: `{"Biology", "Chemistry", "Medicine"}`