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Approach:

The TextSimpleCategoryLLM model is a GPT-2 based language model trained to generate text responses based on input prompts, focusing on a simple categorization task. The model utilizes the GPT-2 architecture, fine-tuned on a dataset consisting of text prompts paired with corresponding categories. During training, the model learns to generate text that aligns with the specified category, enabling it to provide relevant information within the given context. This approach facilitates tasks such as text completion and question answering within defined categories, offering users a straightforward and effective tool for generating context-aware text responses.

Trained with:

    label	category

count 32998 32998 unique 31872 3 freq 20 1299

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F32
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Dataset used to train AkilanSelvam/spinsnow-problem-categorizer