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update readme.md, add context

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@@ -32,7 +32,7 @@ This model is suitable for applications in education, literary analysis, and sto
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  ## Model Architecture
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  - **Base Model**: `bert-base-uncased`
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  - **Classification Layer**: A fully connected layer on top of BERT for 7-class classification.
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- - **Input**: Question text (e.g., "Who is the main character in the story?" or "why could n't alice get a doll as a child ? \<SEP> because her family was very poor " )
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  - **Output**: Predicted label and confidence score.
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  ---
 
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  ## Model Architecture
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  - **Base Model**: `bert-base-uncased`
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  - **Classification Layer**: A fully connected layer on top of BERT for 7-class classification.
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+ - **Input**: Question text (e.g., "Who is the main character in the story?")、QA text (e.g. "why could n't alice get a doll as a child ? \<SEP> because her family was very poor ")、 QA pair + Context(e.g. "why could n't alice get a doll as a child ? \<SEP> because her family was very poor \<context> alice is ... ")
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  - **Output**: Predicted label and confidence score.
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  ---