In this article, we review the paper on MambaOut and explore the nature of Mamba. We will delve into the potential of MambaOut and test the model using Paperspace.
In this tutorial, we discuss the new IDM-VTON application, discuss some improvements we have added with Grounded Segment Anything, and show off some examples of the models potential.
Experiment with new hairstyle and haircolor, with HairFastGAN. A novel approach to transfer a hairstyle from a reference image to another for virtual hair try-on.
In this tutorial, we look at Baidu's RT-DETR object detection framework, and show how to implement it in a Paperspace Notebook.
In this tutorial, we break down and show how to use the foundation model, Vision Transformers. Additionally, we provide a code demo to use ViT for Image Recognition.
In this tutorial, we introduce PixArt Alpha - the latest open source model for text-to-image generation to hit the market and give Stable Diffusion a challenger!
In part 2 of this series on aleatoric uncertainty, we implement a solution with TensorFlow Probability.
In this tutorial we will demonstrate the training of the YOLOv8 model using a custom dataset, evaluating its performance in predicting and analyzing web images. Additionally, this tutorial provides an overview of the YOLO model and its evolutionary advancements.
In this tutorial, we understand the MDP model for text-guided image editing and show how you can try the model with a ready-to-use codebase on the Gradient Notebook.
