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Add model's description and input data formatting

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  Download <font color="IndianRed">template excel sheet</font> from here: https://huggingface.co/cbdb/MetaDis/blob/main/template.xlsx
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  ### <font color="IndianRed">Authors </font>
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  Queenie Luo (queenieluo[at]g.harvard.edu)
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  <br>
 
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  Download <font color="IndianRed">template excel sheet</font> from here: https://huggingface.co/cbdb/MetaDis/blob/main/template.xlsx
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+ ---
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+ ### <font color="IndianRed">MetaDis: Classical Chinese Biographical Metadata Disambiguation </font>
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+ Welcome to the repository for MetaDis, a specialized model designed for disambiguating biographical metadata within Classical Chinese texts.
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+ At the core of the problem MetaDis aims to solve is a common issue researchers encounter when studying historical texts - the identification of individuals sharing the same name. Are these instances referring to the same person or two different people? This is the question MetaDis seeks to answer.
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+ MetaDis is based on the `AutoModelForNextSentencePrediction` architecture, a machine learning model that processes two sequences of data as its input. It then outputs a 0 or 1 - a binary representation indicating whether or not the two sequences refer to the same person. Here, 0 represents 'not the same person', and 1 indicates 'the same person'.
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+ ---
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+ ### <font color="IndianRed">Input Data Formatting </font>
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+ In order to ensure the highest accuracy and performance of the MetaDis model, we've specifically designed an input format based on the data the model was originally trained on. This is crucial as it allows the model to accurately interpret and process your data.
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+ To assist you in this process, we've provided a template Excel (.xlsx) file. We recommend downloading this template and inputting your data directly into it, ensuring your data matches the same format as the model's training data.
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+ To download our Excel data template, please click [here](https://huggingface.co/cbdb/MetaDis/blob/main/template.xlsx).
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+ ---
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  ### <font color="IndianRed">Authors </font>
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  Queenie Luo (queenieluo[at]g.harvard.edu)
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  <br>