Get Started with AI on AMD Platforms#
AMD is uniquely position to run AI models in the breath of its technology.
In this page, we will focus on AI inference on the different AMD technologies. We will show you how to run pre-trained models from popular model hubs such as HuggingFace, PyTorch Hub, etc. In the getting started we will mostly focus on the model functionality and how to run it on AMD technologies, model architecture and deeper understanding of the model internals will be covered in a different section.
PyTorch is our framework of choice for most of these resources due to its huge popularity, however, you will be able to find similar examples in any of the other popular AI frameworks.
Requisites#
CPUs: AMD EPYC™ Processors AMD Ryzen™ Processors AMD Ryzen™ AI Processors
Or
GPUs: AMD Instinct™ Accelerators AMD Radeon™ RX Graphics Cards AMD Radeon™ PRO Graphics Cards
Run Pre-trained Models#
We provide a number of notebooks where you can run pre-trained models.
At the top of the notebook we will provide a tag of the technologies where the notebook can be run on using the following colors.
Direct support Can run on systems with enough memory
Check out:
- Using Hugging Face pre-trained models
- MNIST Classification with an MLP Hugging Face Model
- Semantic Segmentation
- Image Classification using Yolov10
- Fine-tuned LAnguage Net Text-To-Text Transfer Transformer
- Google Enhanced Multimodal Machine Learning 2
- OpenAI Whisper - Speech Recognition
- Phi-3-vision Instruct Open Multimodal Model
- Phi-3 Instruct Open Model
- Using PyTorch Hub Models
- Generative AI on AMD platforms
More Resources#
List of extra resources listed in no particular order.
Efficient image generation with Stable Diffusion models and ONNX Runtime using AMD GPUs
How to run a Large Language Model (LLM) on your AMD Ryzen™ AI PC or Radeon™ Graphics Card
Experience Meta Llama 3 with AMD Ryzen™ AI and Radeon™ 7000 Series Graphics
Automatic1111 Stable Diffusion WebUI with DirectML Extension on AMD GPUs
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