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feat: add LCM scheduler (#983)
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@@ -107,8 +107,8 @@ Options:
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compatibility issues with quantized parameters, but it usually offers faster inference
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speed and, in some cases, lower memory usage. The at_runtime mode, on the other
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hand, is exactly the opposite.
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--scheduler denoiser sigma scheduler, one of [discrete, karras, exponential, ays, gits, smoothstep, sgm_uniform, simple], default:
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discrete
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--scheduler denoiser sigma scheduler, one of [discrete, karras, exponential, ays, gits, smoothstep, sgm_uniform, simple, lcm],
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default: discrete
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--skip-layers layers to skip for SLG steps (default: [7,8,9])
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--high-noise-sampling-method (high noise) sampling method, one of [euler, euler_a, heun, dpm2, dpm++2s_a, dpm++2m, dpm++2mv2, ipndm, ipndm_v, lcm,
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ddim_trailing, tcd] default: euler for Flux/SD3/Wan, euler_a otherwise
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@@ -1197,7 +1197,7 @@ void parse_args(int argc, const char** argv, SDParams& params) {
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on_lora_apply_mode_arg},
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{"",
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"--scheduler",
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"denoiser sigma scheduler, one of [discrete, karras, exponential, ays, gits, smoothstep, sgm_uniform, simple], default: discrete",
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"denoiser sigma scheduler, one of [discrete, karras, exponential, ays, gits, smoothstep, sgm_uniform, simple, lcm], default: discrete",
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on_scheduler_arg},
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{"",
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"--skip-layers",
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