Replies: 2 comments
-
You can use pipeline = StableDiffusionXLPipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0",
torch_dtype=torch.float16,
variant="fp16",
).to("cuda")
generator = torch.Generator(device="cpu").manual_seed(0)
tensor = pipeline(
prompt="a cat", negative_prompt="", num_inference_steps=20, generator=generator, output_type="pt"
).images[0] |
Beta Was this translation helpful? Give feedback.
0 replies
-
It works, thanks! |
Beta Was this translation helpful? Give feedback.
0 replies
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Uh oh!
There was an error while loading. Please reload this page.
-
Hello,
I was wondering if there's a way that when doing inference
image = pipe(prompt).images[0]
it returns the image as Tensor array instead of the options of a numpy array or a pil image.Thanks,
Joan
Beta Was this translation helpful? Give feedback.
All reactions