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Update __init__.py

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tin2tin 9 months ago committed by GitHub
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1 changed files with 69 additions and 9 deletions
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      __init__.py

74
__init__.py
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@ -1138,6 +1138,7 @@ class GeneratorAddonPreferences(AddonPreferences):
"Dreamshaper v8 (1024 x 1024)",
"Lykon/dreamshaper-8",
),
("Lykon/dreamshaper-xl-lightning", "Dreamshaper XL-Lightning (1024 x 1024)", "Lykon/dreamshaper-xl-lightning"),
(
"stabilityai/stable-diffusion-xl-base-1.0",
"Stable Diffusion XL 1.0 (1024x1024)",
@ -1181,6 +1182,7 @@ class GeneratorAddonPreferences(AddonPreferences):
"Proteus (1024x1024)",
"dataautogpt3/ProteusV0.3",
),
("dataautogpt3/ProteusV0.3-Lightning", "ProteusV0.3-Lightning (1024 x 1024)", "dataautogpt3/ProteusV0.3-Lightning"),
("dataautogpt3/OpenDalleV1.1", "OpenDalle (1024 x 1024)", "dataautogpt3/OpenDalleV1.1"),
# ("h94/IP-Adapter", "IP-Adapter (512 x 512)", "h94/IP-Adapter"),
#("PixArt-alpha/PixArt-XL-2-1024-MS", "PixArt (1024 x 1024)", "PixArt-alpha/PixArt-XL-2-1024-MS"),
@ -3551,7 +3553,8 @@ class SEQUENCER_OT_generate_image(Operator):
pipe.enable_model_cpu_offload()
else:
pipe.to(gfx_device)
elif do_convert == False and image_model_card == "Lykon/dreamshaper-xl-lightning":
pipe = AutoPipelineForText2Image.from_pretrained('Lykon/dreamshaper-xl-lightning', torch_dtype=torch.float16, variant="fp16")
# Wuerstchen
elif image_model_card == "warp-ai/wuerstchen":
@ -3760,23 +3763,51 @@ class SEQUENCER_OT_generate_image(Operator):
)
elif image_model_card == "ByteDance/SDXL-Lightning":
import torch
from diffusers import StableDiffusionXLPipeline, EulerDiscreteScheduler
from diffusers import StableDiffusionXLPipeline, EulerAncestralDiscreteScheduler, AutoencoderKL
from huggingface_hub import hf_hub_download
base = "stabilityai/stable-diffusion-xl-base-1.0"
repo = "ByteDance/SDXL-Lightning"
ckpt = "sdxl_lightning_2step_lora.safetensors" # Use the correct ckpt for your step setting!
vae = AutoencoderKL.from_pretrained(
"madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16
)
# Load model.
pipe = StableDiffusionXLPipeline.from_pretrained(base, torch_dtype=torch.float16, variant="fp16").to("cuda")
pipe = StableDiffusionXLPipeline.from_pretrained(base, torch_dtype=torch.float16, vae=vae, variant="fp16").to("cuda")
pipe.load_lora_weights(hf_hub_download(repo, ckpt))
pipe.fuse_lora()
# Ensure sampler uses "trailing" timesteps.
pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing")
pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing")
elif image_model_card == "dataautogpt3/ProteusV0.3-Lightning":
import torch
from diffusers import (
StableDiffusionXLPipeline,
EulerAncestralDiscreteScheduler,
AutoencoderKL
)
# Load VAE component
vae = AutoencoderKL.from_pretrained(
"madebyollin/sdxl-vae-fp16-fix",
torch_dtype=torch.float16
)
# Configure the pipeline
pipe = StableDiffusionXLPipeline.from_pretrained(
"dataautogpt3/ProteusV0.3-Lightning",
vae=vae,
torch_dtype=torch.float16
)
pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
pipe.to('cuda')
elif image_model_card == "dataautogpt3/ProteusV0.3":
from diffusers import StableDiffusionXLPipeline, KDPM2AncestralDiscreteScheduler
from diffusers import StableDiffusionXLPipeline, EulerAncestralDiscreteScheduler
from diffusers import AutoencoderKL
vae = AutoencoderKL.from_pretrained(
@ -3788,7 +3819,7 @@ class SEQUENCER_OT_generate_image(Operator):
torch_dtype=torch.float16,
#variant="fp16",
)
pipe.scheduler = KDPM2AncestralDiscreteScheduler.from_config(pipe.scheduler.config)
pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
pipe.to(gfx_device)
elif image_model_card == "stabilityai/stable-cascade":
@ -3858,10 +3889,16 @@ class SEQUENCER_OT_generate_image(Operator):
scene.movie_num_guidance = 0
pipe.load_lora_weights("segmind/Segmind-VegaRT")
pipe.fuse_lora()
elif image_model_card != "PixArt-alpha/PixArt-XL-2-1024-MS" and image_model_card != "Lykon/dreamshaper-8" and image_model_card != "stabilityai/stable-cascade":
elif image_model_card == "Lykon/dreamshaper-8":
from diffusers import EulerAncestralDiscreteScheduler
pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
elif image_model_card != "PixArt-alpha/PixArt-XL-2-1024-MS" and image_model_card != "stabilityai/stable-cascade":
pipe.scheduler = DPMSolverMultistepScheduler.from_config(
pipe.scheduler.config
)
if image_model_card != "stabilityai/stable-cascade":
pipe.watermark = NoWatermark()
@ -4111,6 +4148,17 @@ class SEQUENCER_OT_generate_image(Operator):
generator=generator,
output_type="pil",
).images[0]
elif image_model_card == "Lykon/dreamshaper-xl-lightning" and do_convert == False:
image = pipe(
prompt=prompt,
negative_prompt=negative_prompt,
num_inference_steps=4,
guidance_scale=2,
height=y,
width=x,
generator=generator,
output_type="pil",
).images[0]
# OpenPose
elif image_model_card == "lllyasviel/sd-controlnet-openpose":
@ -4284,6 +4332,18 @@ class SEQUENCER_OT_generate_image(Operator):
num_inference_steps=2,
).images[0]
decoder = None
elif image_model_card == "dataautogpt3/ProteusV0.3-Lightning":
image = pipe(
prompt=prompt,
negative_prompt=negative_prompt,
height=y,
width=x,
guidance_scale=1.0,
output_type="pil",
num_inference_steps=4,
).images[0]
decoder = None
elif image_model_card == "stabilityai/stable-cascade":
#import torch
prior = StableCascadePriorPipeline.from_pretrained("stabilityai/stable-cascade-prior", torch_dtype=torch.bfloat16)

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