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ROCm

productactiverocm-8ab0db11·4 events·first seen 28d ago

Aliases: ROCm

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Recent events (4)

4Hugging Face Blog·28d ago·source ↗

Easily Build and Share ROCm Kernels with Hugging Face

Hugging Face has published a guide and tooling for building and sharing custom ROCm kernels on its platform, targeting AMD GPU users in the ML ecosystem. The post covers the workflow for packaging, uploading, and reusing ROCm-based GPGPU kernels via the Hub. This lowers the barrier for AMD GPU kernel development and sharing, complementing the existing CUDA-centric kernel ecosystem. The initiative is relevant to inference optimization and the broader push to diversify GPU hardware support in AI workloads.

4Hugging Face Blog·28d ago·source ↗

Run a ChatGPT-like Chatbot on a Single GPU with ROCm

Hugging Face published a guide demonstrating how to run a large language model chatbot on a single AMD GPU using ROCm, AMD's open-source GPU compute stack. The post covers setup, model loading, and inference on AMD hardware as an alternative to NVIDIA CUDA-based workflows. This is relevant to the growing interest in democratizing LLM inference beyond NVIDIA's ecosystem.

5Hugging Face Blog·28d ago·source ↗

Creating Custom Kernels for the AMD MI300

A Hugging Face blog post details the process of writing custom GPU kernels targeting the AMD MI300 accelerator. The post covers practical techniques for optimizing AI workloads on AMD hardware, contributing to the growing ecosystem of non-NVIDIA GPU support for ML inference and training. This is relevant to the broader trend of diversifying AI infrastructure beyond CUDA-dominant workflows.

5Hugging Face Blog·28d ago·source ↗

AMD + Hugging Face: Large Language Models Out-of-the-Box Acceleration with AMD GPU

Hugging Face and AMD announced integration work enabling out-of-the-box LLM acceleration on AMD GPUs via the Optimum library. The collaboration targets ROCm-based AMD hardware, aiming to reduce friction for users running inference on non-NVIDIA GPU stacks. This represents a continued push to broaden the hardware ecosystem available to open-weights model users.