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app.py
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gr.Markdown(
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"""
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<div style="text-align: center;">
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<h1>SynthGenAI Dataset Generator</h1>
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</div>
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"""
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gr.Markdown(
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with gr.Row():
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gr.Markdown(
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"""
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<div style="text-align: center;">
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
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<h1>SynthGenAI Dataset Generator</h1>
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</div>
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""",
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elem_id="header"
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gr.Markdown(
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"""
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<div style="text-align: center;">
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## Overview π§
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SynthGenAI is designed to be modular and can be easily extended to include different API providers for LLMs and new features.
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## Why SynthGenAI? π€
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Interest in synthetic data generation has surged recently, driven by the growing recognition of data as a critical asset in AI development. Synthetic data generation addresses challenges by allowing us to create diverse and useful datasets using current pre-trained Large Language Models (LLMs).
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[GitHub Repository](https://github.com/Shekswess/synthgenai/tree/main) | [Documentation](https://shekswess.github.io/synthgenai/)
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</div>
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""",
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elem_id="overview"
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with gr.Row():
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