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Introduces a third hardware mode alongside CUDA and CPU: ROCm (AMD GPU). AMD GPUs present as CUDA devices under PyTorch ROCm, so the existing GPU path is reused with minimal changes — the main additions are wheel management, device detection, and suppressing flash_attn (unsupported on ROCm). - server/vibevoice_server.py: extend _resolve_device() to recognise 'rocm' (auto-detected via torch.version.hip); add _torch_device() helper that maps 'rocm' → 'cuda' for all PyTorch API calls; apply GPU optimisations for both cuda and rocm in _init_model(); always use sdpa on ROCm; propagate _torch_device() to _load_voice_presets() map_location. - server/start.sh: add --rocm flag; sync .venv-rocm with uv sync --no-sources then replace torch with the ROCm 6.2 wheel via uv pip install; set VIBEPOD_DEVICE=rocm for uvicorn. - server/pyproject.toml: register pytorch-rocm62 index (explicit); add .venv-rocm to ruff excludes. - package.json: add dev:rocm and dev:server:rocm scripts. - README.md: document ROCm mode, prerequisites (RX 6000+, ROCm 6.2+, Linux), and new commands; expand CUDA vs CPU section to CUDA vs CPU vs ROCm. https://claude.ai/code/session_0168pSswiaoEf6LEx6UQWfBu