# Images of Parti Prompts for "if-v-1.0"

Code that was used to get the results:

```py
from diffusers import DiffusionPipeline
import torch

pipe_low = DiffusionPipeline.from_pretrained("DeepFloyd/IF-I-XL-v1.0", safety_checker=None, watermarker=None, torch_dtype=torch.float16, variant="fp16")
pipe_low.enable_model_cpu_offload()

pipe_up = DiffusionPipeline.from_pretrained("DeepFloyd/IF-II-L-v1.0", safety_checker=None, watermarker=None, text_encoder=pipe_low.text_encoder, torch_dtype=torch.float16, variant="fp16")
pipe_up.enable_model_cpu_offload()

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

prompt_embeds, negative_prompt_embeds = pipe_low.encode_prompt(prompt)
images = pipe_low(prompt_embeds=prompt_embeds, negative_prompt_embeds=negative_prompt_embeds, num_inference_steps=100, generator=generator, output_type="pt").images
images = pipe_up(prompt_embeds=prompt_embeds, negative_prompt_embeds=negative_prompt_embeds, image=images, num_inference_steps=100, generator=generator).images[0]
```
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{"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": 166170790.0, "num_examples": 1632}], "download_size": 166034308, "dataset_size": 166170790.0}}
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# Images of Parti Prompts for "if-v-1.0"

Code that was used to get the results:


# Images of Parti Prompts for "if-v-1.0"

Code that was used to get the results:
TAGS
#region-us 
 # Images of Parti Prompts for "if-v-1.0"

Code that was used to get the results:
passage: TAGS
#region-us 
# Images of Parti Prompts for "if-v-1.0"

Code that was used to get the results: