Disty0/sotediffusion-wuerstchen3

Instalación y uso básico con Diffusers:

pip install -U diffusers transformers accelerate

import torch
from diffusers import DiffusionPipeline

# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Disty0/sotediffusion-wuerstchen3", dtype=torch.bfloat16, device_map="cuda")

prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]

Ejemplo recomendado con StableCascadeCombinedPipeline y el decoder:

pip install diffusers

import torch
from diffusers import StableCascadeCombinedPipeline

device = "cuda"
dtype = torch.bfloat16 # or torch.float16
model = "Disty0/sotediffusion-wuerstchen3-decoder"

pipe = StableCascadeCombinedPipeline.from_pretrained(model, torch_dtype=dtype)

# send everything to the gpu:
pipe = pipe.to(device, dtype=dtype)
pipe.prior_pipe = pipe.prior_pipe.to(device, dtype=dtype)

# or enable model offload to save vram:
# pipe.enable_model_cpu_offload()

prompt = "newest, extremely aesthetic, best quality, 1girl, solo, cat ears, pink hair, orange eyes, long hair, bare shoulders, looking at viewer, smile, indoors, casual, living room, playing guitar,"
negative_prompt = "very displeasing, worst quality, monochrome, realistic, oldest, loli,"

output = pipe(
    width=1024,
    height=1536,
    prompt=prompt,
    negative_prompt=negative_prompt,
    decoder_guidance_scale=2.0,
    prior_guidance_scale=7.0,
    prior_num_inference_steps=30,
    output_type="pil",
    num_inference_steps=10
).images[0]

## do something with the output image

Parámetros sugeridos para SD.Next: sampler por defecto, 30 o 40 pasos, 10 pasos de refiner, CFG 7, CFG secundario 1 o 2, y prompt negativo con realistic cuando el modelo derive hacia imágenes realistas.