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A blueprint for AI development, focusing on applied examples of RAG, information extraction, analysis and fine-tuning in the age of LLMs. It is a more practical approach that strives to show the application of some of the theoretical learnings from [the smol-course](https://github.com/huggingface/smol-course) as an end2end real-world problem.
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> π Web apps and microservices included!
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> Each notebook will show how to deploy your AI as a [webapp on Hugging Face Spaces with Gradio](https://huggingface.co/docs/hub/en/spaces-sdks-gradio), which you can directly use as microservices through [the Gradio Python Client](https://www.gradio.app/guides/getting-started-with-the-python-client). All the code and demos can be used in a private or public setting. [Deployed on the Hub!](https://huggingface.co/smol-blueprint)
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[Code on GitHub](https://github.com/huggingface/smol-blueprint)
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