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[https://github.com/ollama/ollama/issues/2637] - - public:mzimmerm
amd, apu, gfx900, install, pytorch, rocm - 6 | id:1491350 -

Latest (0.1.27) docker image with ROCm works for me on Ryzen 5600G with 8GB VRAM allocation. Prompt processing is 2x faster than with CPU. Generation runs at max speed even if CPU is busy running other processes. I am on Fedora 39. Container setup: HSA_OVERRIDE_GFX_VERSION=9.0.0

[https://medium.com/@rafaelmanzanom/ditching-cuda-for-amd-rocm-for-more-accessible-llm-inference-ryzen-apus-edition-92c3649f8f7d] - - public:mzimmerm
ai, amd, apu, compile, gfx902, install, pytorch, rocm - 8 | id:1489810 -

Train LLM on AMD APU. In this scenario, we’ll use an APU because most laptops with a Ryzen CPU include an iGPU; specifically, this post should work with iGPUs based on the “GCN 5.0” architecture, or “Vega” for friends. We’ll use an AMD Ryzen 2200G in this post, an entry-level processor equipped with 4C/4T and an integrated GPU.

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