f98a06b72b
The three train_precision_modes capability tests patched is_available and get_device_capability but not is_bf16_supported, so on the CPU-only CI runner (where the real probe is False) the dense modes collapsed to nf4 and the fp8 / mxfp8 assertions failed; they only passed on a bf16 GPU dev box. An Ada or Blackwell GPU is by definition bf16-capable, so the helper must stub it True to exercise the capability gate the tests target. |
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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 | ||