Project Description
The goal is to have a language model, that is able to answer technical questions on Uyuni. Uyuni documentation is too large for in-context processing, so finetuning is the way to go.
Goal for this Hackweek
Finetune a model based on llama-2-7b.
Resources
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This project is part of:
Hack Week 23
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Description
I want to setup a Radeon RX 9600 XT 16 GB at home with ROCm on Slowroll.
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I want to test how fast AI inference can get with the GPU and if I can use LoRA to re-train an existing free model for some task.
Resources
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Results
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HIPCXX="$(hipconfig -l)/clang" HIP_PATH="$(hipconfig -R)" \
cmake -S . -B build -DGGML_HIP=ON -DAMDGPU_TARGETS=$LLAMACPP_ROCM_ARCH \
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-Dhipblas_DIR=/usr/lib64/cmake/hipblaslt/ \
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m=models/gpt-oss-20b-mxfp4.gguf
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Without the --device option it faulted. Maybe because my APU also appears there?
I updated/fixed various related packages: https://src.opensuse.org/ROCm/rocm-examples/pulls/1 https://src.opensuse.org/ROCm/hipblaslt/pulls/1 SR 1320959
benchmark
I benchmarked inference with llama.cpp + gpt-oss-20b-mxfp4.gguf and ROCm offloading to a Radeon RX 9060 XT 16GB. I varied the number of layers that went to the GPU:
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Resources
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Resources
Gemini CLI setup:
~/.gemini/settings.json:
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Resources