22dad1df73
The start route's precision preflight folded bf16/int8/fp8 into the CUDA requirement but omitted mxfp8, so an mxfp8 request on a GPU-less host (or an older CUDA GPU without Blackwell) passed the preflight, evicted resident image and chat models, then raised only in the spawned trainer child. Mirror _resolve_base_precision: require CUDA for mxfp8 and re-check the Blackwell (sm100+) capability up front, so a doomed run is rejected before teardown. |
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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 | ||