Posts tagged Images

Inferencing with AI2’s OLMo model on AMD GPU

In this blog, we will show you how to generate text using AI2’s OLMo model on AMD GPU.

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ResNet for image classification using AMD GPUs

In this blog, we demonstrate training a simple ResNet model for image classification on AMD GPUs using ROCm on the CIFAR10 dataset. Training a ResNet model on AMD GPUs is simple, requiring no additional work beyond installing ROCm and appropriate PyTorch libraries.

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Image classification using Vision Transformer with AMD GPUs

The Vision Transformer (ViT) model was first proposed in An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. ViT is an attractive alternative to conventional Convolutional Neural Network (CNN) models due to its excellent scalability and adaptability in the field of computer vision. On the other hand, ViT can be more expensive compared to CNN for large input images as it has quadratic computation complexity with respect to input size.

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Efficient image generation with Stable Diffusion models and ONNX Runtime using AMD GPUs

In this blog, we show you how to use pre-trained Stable Diffusion models to generate images from text (text-to-image), transform existing visuals (image-to-image), and restore damaged pictures (inpainting) on AMD GPUs using ONNX Runtime.

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Two-dimensional images to three-dimensional scene mapping using NeRF on an AMD GPU

This tutorial aims to explain the fundamentals of NeRF and its implementation in PyTorch. The code used in this tutorial is inspired by Mason McGough’s colab notebook and is implemented on an AMD GPU.

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Efficient image generation with Stable Diffusion models and AITemplate using AMD GPUs

Stable Diffusion has emerged as a groundbreaking advancement in the field of image generation, empowering users to translate text descriptions into captivating visual output.

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