README.md

metadata

dataset_info:
  features:
    - name: Prompt
      dtype: string
    - name: Category
      dtype: string
    - name: Challenge
      dtype: string
    - name: Note
      dtype: string
    - name: images
      dtype: image
    - name: model_name
      dtype: string
    - name: seed
      dtype: int64
  splits:
    - name: train
      num_bytes: 198852412
      num_examples: 1632
  download_size: 198704477
  dataset_size: 198852412

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)