Design your own model on AMD Platforms

In this page, we will focus on designing, training and validating your own model on AMD CPUs and GPUs. We will show you how to use PyTorch to define and train your model.

Technologies covered: CPU, GPU.

Requisites

GPUs: AMD Instinct™ Accelerators, AMD Radeon™ RX Graphics Cards or AMD Radeon™ PRO Graphics Cards

Setup environment.

Examples

• Create Mandelbrot Dataset
• Mandelbrot Multi-Layer Perceptron Model
• Machine Learning Training and Inference with PyTorch
• Model Training for Pneumonia Detection
• Train YOLOv8 on a Custom Dataset using CLI

Resources

• ResNet for image classification using AMD GPUs

• Question-answering Chatbot with LangChain on an AMD GPU

• Building a decoder transformer model on AMD GPU(s)

• Simplifying deep learning: A guide to PyTorch Lightning

• Training a Neural Collaborative Filtering (NCF) Recommender on an AMD GPU

• ResNet for image classification using AMD GPUs

If you would like to suggest a resource, email us aup@amd.com

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SPDX-License-Identifier: MIT