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v0.1.0: AMD Instinct GPUs, Ryzen AI preliminary support

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@fxmarty fxmarty released this 06 Dec 10:20
· 58 commits to main since this release

We are glad to release the first version of Optimum-AMD, extending the support of Hugging Face libraries for AMD ROCm GPUs and Ryzen AI laptops. More to come in the coming weeks!

RyzenAIModelForImageClassification for Ryzen AI NPU

Optimum-AMD allows to leverage the Ryzen AI NPU (Neural Processing Unit) for image classification through the RyzenAIModelForImageClassification class for faster local inference. Check out the documentation for more details!

amdrun wrapper on torchrun to dispatch on the most optimal GPUs

When using multiple GPUs that need to communicate (tensor parallel, data parallel, etc.), the choice of which devices is used is crutial for optimal performances. amdrun command line that comes along Optimum-AMD allows to automatically dispatch a torchrun job on a single node to the optimal devices:

amdrun --ngpus <num_gpus> <script> <script_args>

ONNX Runtime ROCMExecutionProvider support

Optimum ONNX Runtime integration supports ROCm natively: https://huggingface.co/docs/optimum/onnxruntime/usage_guides/amdgpu

Text Generation Inference library for LLM inference supports ROCm

Text Generation Inference supports ROCm natively: https://huggingface.co/docs/text-generation-inference/quicktour

GPTQ quantization support

AutoGPTQ library supports ROCm natively: https://github.com/PanQiWei/AutoGPTQ#quick-installation

Flash Attention 2 support for ROCm

Transformers supports natively Flash Attention 2 for ROCm: https://huggingface.co/docs/transformers/main/en/perf_infer_gpu_one#flashattention-2

What's Changed

New Contributors

Full Changelog: https://github.com/huggingface/optimum-amd/commits/v0.1.0