WIBE-HuggingFace/stable-diffusion-2-1-base

Instalación y uso con Diffusers para el repositorio WIBE-HuggingFace:

pip install -U diffusers transformers accelerate

import torch
from diffusers import DiffusionPipeline

# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained(
    "WIBE-HuggingFace/stable-diffusion-2-1-base",
    dtype=torch.bfloat16,
    device_map="cuda"
)

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

Ejemplo alternativo con Stable Diffusion 2 base y scheduler Euler:

pip install diffusers transformers accelerate scipy safetensors

from diffusers import StableDiffusionPipeline, EulerDiscreteScheduler
import torch

model_id = "stabilityai/stable-diffusion-2-base"

# Use the Euler scheduler here instead
scheduler = EulerDiscreteScheduler.from_pretrained(model_id, subfolder="scheduler")
pipe = StableDiffusionPipeline.from_pretrained(
    model_id,
    scheduler=scheduler,
    torch_dtype=torch.float16
)
pipe = pipe.to("cuda")

prompt = "a photo of an astronaut riding a horse on mars"
image = pipe(prompt).images[0]
image.save("astronaut_rides_horse.png")

Para GPUs con poca VRAM, se recomienda activar pipe.enable_attention_slicing() después de mover el pipeline a CUDA; para mejor rendimiento, la tarjeta sugiere instalar xformers.