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diffusers-parti-prompts/sd-v1-5

Images of Parti Prompts for "sd-v1-5" Code that was used to get the results: from diffusers import DiffusionPipeline, DDIMScheduler import torch import PIL pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16, safety_checker=None) pipe.to("cuda") pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config) prompt = "" # a parti prompt generator = torch.Generator("cuda").manual_seed(0) image = pipe(prompt… See the full description on the dataset page: https://huggingface.co/datasets/diffusers-parti-prompts/sd-v1-5.

sourceHugging Faceupdated 3y agoView on Hugging Face

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Images of Parti Prompts for "sd-v1-5"

Code that was used to get the results:

from diffusers import DiffusionPipeline, DDIMScheduler
import torch
import PIL

pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16, safety_checker=None)
pipe.to("cuda")
pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config)

prompt = "" # a parti prompt
generator = torch.Generator("cuda").manual_seed(0)

image = pipe(prompt, generator=generator, num_inference_steps=100, guidance_scale=7.5).images[0]
image = image.resize((256, 256), resample=PIL.Image.Resampling.LANCZOS)