Raphaël SemeteysA new way of learning a framework, a deep dive into PageIndex’s vectorless reasoning-based RAG, and a real build that searches a personal Google Drive library without paying for LLM tokens.
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Raphaël SemeteysA structured, data-driven comparison of today’s leading open-source engines for serving AI models.
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Raphaël SemeteysIn the first two parts of this series, we explored Stable Diffusion, ComfyUI, and how to build Text-to-Image and Image-to-Image workflows to generate images of Yoga poses. With the help of ControlNets, we learned how to transfer a pose from an abstract reference image to our final generated image.
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Raphaël SemeteysIn the first part of this series on image generation, we explored how to set up a simple Text-to-Image workflow using Stable Diffusion and ComfyUI, running it locally. We also introduced embeddings to enhance prompts and adjust image styles. However, we found that embeddings alone were not sufficient for our specific use case: generating accurate yoga poses.
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Raphaël SemeteysIn this series of articles, I will introduce image generation using Stable Diffusion and ComfyUI. This first article discusses the theory and provides basic examples. My goal is to generate precise images of yoga poses using only your local machine. Due to legal restrictions, I cannot use images from the Internet. Given these limitations, how can generative AI assist?
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Raphaël Semeteys
Luxin ZhangEmbarking on the second and last part of our ‘Generative AI Openness’ series, we earlier established a straightforward framework to gauge the openness of Large Language Models (LLMs) and utilized it to explore LLM development and the positioning of key players. We noticed a trend towards increasingly restricted LLM artifacts for OpenAI and Google, contrasted with Meta’s more open approach.
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