# Images of Parti Prompts for "sd-v2.1"

Code that was used to get the results:

```py
from diffusers import DiffusionPipeline, DDIMScheduler
import torch
import PIL

pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1", 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)
```

region:us
{"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": 191652463.0, "num_examples": 1632}], "download_size": 191500777, "dataset_size": 191652463.0}}
TAGS
#region-us 

# Images of Parti Prompts for "sd-v2.1"

Code that was used to get the results:



# Images of Parti Prompts for "sd-v2.1"

Code that was used to get the results:
TAGS
#region-us 
 # Images of Parti Prompts for "sd-v2.1"

Code that was used to get the results:
passage: TAGS
#region-us 
# Images of Parti Prompts for "sd-v2.1"

Code that was used to get the results: