This repository contains tasks focusing on prompt engineering for vision models. Each task explores different aspects of image segmentation, object detection, and image generation using advanced machine learning models. Below are detailed descriptions of the tasks and their respective notebooks.
Colab notebook for Stable Diffusion Hyper-SDXL.
A tutorial that guides users through the process of fine-tuning a stable diffusion model using HuggingFace's diffusers library. The tutorial includes advice on suitable hardware requirements, data preparation using the BLIP Flowers Dataset and a Python notebook, and detailed instructions for fine-tuning the model.
✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing an IMAGINATION proxia when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).
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