DarthAffe/stable-diffusion.cpp
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update lora docs

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leejet committed 2025-11-13 21:43:09 +08:00
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commit f2ec08f4b1
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examples/cli/README.md
+6
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@@ -99,6 +99,12 @@ Options:
--sampling-method sampling method, one of [euler, euler_a, heun, dpm2, dpm++2s_a, dpm++2m, dpm++2mv2, ipndm, ipndm_v, lcm, ddim_trailing,
tcd] (default: euler for Flux/SD3/Wan, euler_a otherwise)
--prediction prediction type override, one of [eps, v, edm_v, sd3_flow, flux_flow]
--lora-apply-mode the way to apply LoRA, one of [auto, immediately, at_runtime], default is auto. In auto mode, if the model weights
contain any quantized parameters, the at_runtime mode will be used; otherwise,
immediately will be used.The immediately mode may have precision and
compatibility issues with quantized parameters, but it usually offers faster inference
speed and, in some cases, lower memory usageThe at_runtime mode, on the other
hand, is exactly the opposite.
--scheduler denoiser sigma scheduler, one of [discrete, karras, exponential, ays, gits, smoothstep, sgm_uniform, simple], default:
discrete
--skip-layers layers to skip for SLG steps (default: [7,8,9])
examples/cli/main.cpp
+3 -2
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@@ -1143,8 +1143,9 @@ void parse_args(int argc, const char** argv, SDParams& params) {
"--lora-apply-mode",
"the way to apply LoRA, one of [auto, immediately, at_runtime], default is auto. "
"In auto mode, if the model weights contain any quantized parameters, the at_runtime mode will be used; otherwise, immediately will be used."
"The immediately mode consumes less GPU memory but may lead to precision loss and compatibility issues. "
"The at_runtime mode uses slightly more memory, but offers better compatibility and higher precision.",
"The immediately mode may have precision and compatibility issues with quantized parameters, "
"but it usually offers faster inference speed and, in some cases, lower memory usage"
"The at_runtime mode, on the other hand, is exactly the opposite.",
on_lora_apply_mode_arg},
{"",
"--scheduler",