from diffusers import DiffusionPipeline, UniPCMultistepScheduler
import torch

pipeline = DiffusionPipeline.from_pretrained(
    "andite/anything-v4.0", torch_dtype=torch.float16, safety_checker=None
).to("cuda")
pipeline.scheduler = UniPCMultistepScheduler.from_config(pipeline.scheduler.config)
# uncomment to download the safetensor weights
#!wget https://civitai.com/models/109643/real-and-animebreast-milklactationbreast-milk-drippingspraying-breast-milkgrabbing-breastsbreast-squeezenipple-pinch-and
pipeline.load_lora_weights("."spraying breast milk_SD1.5v1.safetensors") 
prompt = "masterpiece, illustration, ultra-detailed, cityscape, san francisco, golden gate bridge, california, bay area, in the snow, beautiful detailed starry sky"
negative_prompt = "lowres, cropped, worst quality, low quality, normal quality, artifacts, signature, watermark, username, blurry, more than one bridge, bad architecture"

images = pipeline(
    prompt=prompt,
    negative_prompt=negative_prompt,
    width=512,
    height=512,
    num_inference_steps=25,
    num_images_per_prompt=4,
    generator=torch.manual_seed(0),
).images
from PIL import Image


def image_grid(imgs, rows=2, cols=2):
    w, h = imgs[0].size
    grid = Image.new("RGB", size=(cols * w, rows * h))

    for i, img in enumerate(imgs):
        grid.paste(img, box=(i % cols * w, i // cols * h))
    return grid


image_grid(images)