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Build a Fashion Design Web App with DALL-E, Gradio and SAM | View in the Skills Network Catalog

Build an AI fashion assistant with CLIPSeg, SAM, and DALL·E 2 that lets users virtually try on, restyle, and redesign clothes through text prompts. Use CLIPSeg and SAM to detect and segment clothing items or accessories in any image, then integrate DALL·E 2 to inpaint and redesign those regions from simple text prompts. Experiment with new fabrics, styles, and colors, all generated intelligently and seamlessly. By the end, you’ll have created a shareable web app that empowers anyone to visualize and prototype fashion ideas instantly through the power of computer vision and generative AI.

Fine Tune a Vision Model for Image Classification with LoRA | View in the Skills Network Catalog

Learn to fine-tune a Vision Transformer (ViT) with LoRA (Low-Rank Adapters) for targeted image classification and adapt AI models to your own data for any use case. You might think fine-tuning a model with millions of parameters requires massive compute and memory, not with LoRA. In this guided project, you'll load a pretrained DeiT model using Hugging Face's API, extend its ability to detect new classes, and train it on a custom dataset. You'll learn how parameter-efficient fine-tuning (PEFT) makes adapting large transformer models fast, lightweight, and cost-effective for any use case.