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feat: add performance hyper-sd based on 4step LoRA (#2812)

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* feat: add performance hyper-sd based on 4step LoRA

* feat: use LoRA weight 0.8, sampler dpmpp_sde_gpu and scheduler_name karras

suggested in https://github.com/lllyasviel/Fooocus/discussions/2813#discussioncomment-9245251
results see https://github.com/lllyasviel/Fooocus/discussions/2813#discussioncomment-9275251

* feat: change ByteDance huggingface profile with mashb1t

* wip: add hyper-sd 8 step cfg lora with negative prompt support

* feat: remove hyper-sd8 performance

still waiting for the release of hyper-sd 4step CFG LoRA, not yet satisfied with any of the CFG LoRAs compared to non-cfg ones.
see https://huggingface.co/ByteDance/Hyper-SD
This commit is contained in:
Manuel Schmid
2024-05-19 13:23:08 +02:00
committed by GitHub
parent 2e2e8f851a
commit 13599edb9b
3 changed files with 43 additions and 3 deletions
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modules/async_worker.py
+27
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@@ -275,6 +275,33 @@ def worker():
adm_scaler_negative = 1.0
adm_scaler_end = 0.0
elif performance_selection == Performance.HYPER_SD:
print('Enter Hyper-SD mode.')
progressbar(async_task, 1, 'Downloading Hyper-SD components ...')
loras += [(modules.config.downloading_sdxl_hyper_sd_lora(), 0.8)]
if refiner_model_name != 'None':
print(f'Refiner disabled in Hyper-SD mode.')
refiner_model_name = 'None'
sampler_name = 'dpmpp_sde_gpu'
scheduler_name = 'karras'
sharpness = 0.0
guidance_scale = 1.0
adaptive_cfg = 1.0
refiner_switch = 1.0
adm_scaler_positive = 1.0
adm_scaler_negative = 1.0
adm_scaler_end = 0.0
elif performance_selection == Performance.HYPER_SD8:
print('Enter Hyper-SD8 mode.')
progressbar(async_task, 1, 'Downloading Hyper-SD components ...')
loras += [(modules.config.downloading_sdxl_hyper_sd_cfg_lora(), 0.3)]
sampler_name = 'dpmpp_sde_gpu'
scheduler_name = 'normal'
print(f'[Parameters] Adaptive CFG = {adaptive_cfg}')
print(f'[Parameters] Sharpness = {sharpness}')
print(f'[Parameters] ControlNet Softness = {controlnet_softness}')