taesdxl

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license:mit

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Manojb

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16 downloads

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Quick Summary

TAESDXL is very tiny autoencoder which uses the same "latent API" as SDXL-VAE.

Code Examples

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

Using in 🧨 diffuserspythonpytorch

import torch
from diffusers import DiffusionPipeline, AutoencoderTiny

pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "slice of delicious New York-style cheesecake topped with berries, mint, chocolate crumble"
image = pipe(prompt, num_inference_steps=50, generator=torch.Generator("cpu").manual_seed(0x7A35D)).images[0]
image.save("cheesecake_sdxl.png")

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