0f2f4334e2
The start-route preflight caught the bf16-GPU and int8-torchao requirements but not the dense precisions' CUDA requirement: on a GPU-less host bf16_unsupported_reason exempts CPU-only, so a bf16/fp8 (or int8-with-torchao) DiT request passed the preflight, evicted resident workloads, then raised only in the trainer child. Add the dense-mode CUDA gate mirroring _resolve_base_precision so the doomed run is rejected up front. Also pin bf16_unsupported_reason in the two positive-path family-info tests so they are deterministic across GPU types (a non-bf16 CUDA box would otherwise empty every DiT family's advertised modes). |
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| .. | ||
| backend | ||
| frontend | ||
| src-tauri | ||
| __init__.py | ||
| install_llama_prebuilt.py | ||
| install_node_prebuilt.py | ||
| install_python_stack.py | ||
| install_sd_cpp_prebuilt.py | ||
| LICENSE.AGPL-3.0 | ||
| node_prebuilt_pins.json | ||
| package-lock.json | ||
| package.json | ||
| setup.bat | ||
| setup.ps1 | ||
| setup.sh | ||
| Unsloth_Studio_Colab.ipynb | ||