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  # Model Overview
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- This model is a fine-tuned version of llama3 using the [QueryBridge dataset](https://huggingface.co/datasets/USERNAME/QueryBridge). We utilized **Low-Rank Adaptation (LoRA)** to train it for tagging question components using the tags in the table below. The demo video shows how the mapped question appears and, after converting it to a graph representation, how we visualized it as shown in the video.
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  The tagged questions in the QueryBridge dataset are designed to train language models to understand the components and structure of a question effectively. By annotating questions with specific tags such as `<qt>`, `<p>`, `<o>`, and `<s>`, we provide a detailed breakdown of each question's elements, which aids the model in grasping the roles of different components.
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  ### Prepare the Dataset
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- For this fine-tuning, we utilized the [QueryBridge dataset](https://huggingface.co/datasets/USERNAME/QueryBridge), specifically the pairs of questions and their corresponding tagged questions. However, before we can use this dataset, it is necessary to convert the data into instruct prompts suitable for fine-tuning the model. You can find these prompts at [this link](https://huggingface.co/datasets/aorogat/Questions_to_Tagged_Questions_Prompts). Download the prompts and save them in the directory: `/home/YOUR_USERNAME/data`
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  ### Fine-Tune the Model
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  # Model Overview
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+ This model is a fine-tuned version of llama3 using the [QueryBridge dataset](https://huggingface.co/datasets/aorogat/QueryBridge). We utilized **Low-Rank Adaptation (LoRA)** to train it for tagging question components using the tags in the table below. The demo video shows how the mapped question appears and, after converting it to a graph representation, how we visualized it as shown in the video.
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  The tagged questions in the QueryBridge dataset are designed to train language models to understand the components and structure of a question effectively. By annotating questions with specific tags such as `<qt>`, `<p>`, `<o>`, and `<s>`, we provide a detailed breakdown of each question's elements, which aids the model in grasping the roles of different components.
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  ### Prepare the Dataset
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+ For this fine-tuning, we utilized the [QueryBridge dataset](https://huggingface.co/datasets/aorogat/QueryBridge), specifically the pairs of questions and their corresponding tagged questions. However, before we can use this dataset, it is necessary to convert the data into instruct prompts suitable for fine-tuning the model. You can find these prompts at [this link](https://huggingface.co/datasets/aorogat/Questions_to_Tagged_Questions_Prompts). Download the prompts and save them in the directory: `/home/YOUR_USERNAME/data`
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  ### Fine-Tune the Model
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