5c249ebada
apply_step_cache on the video load path omitted quant_active, so a quantized video transformer (an engaged dense transformer_quant, or a GGUF checkpoint) that also enabled First-Block-Cache without an explicit threshold used the dense bf16 threshold (0.08) instead of the higher quantized threshold (0.12) the cache helper documents as needed for quantized transformers to trigger. The advertised quant plus FBCache path therefore cached far less than intended. Thread quant_active through exactly as the image path (diffusion.py) does: an engaged transformer_quant or a GGUF transformer both count as quant-active here. |
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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 | ||