Removing the memory-intensive 4.7B parameter T5-XXL text encoder during inference can significantly decrease the memory requirements for SD3 with only a slight loss in performance.  
```python
import torch
from diffusers import StableDiffusion3Pipeline

pipe = StableDiffusion3Pipeline.from_pretrained(
"stabilityai/stable-diffusion-3-medium-diffusers",
text_encoder_3=None,
tokenizer_3=None,
torch_dtype=torch.float16
)
pipe.to("cuda")

image = pipe(
prompt="a photo of a cat holding a sign that says hello world",
negative_prompt="",
num_inference_steps=28,
height=1024,
width=1024,
guidance_scale=7.0,
).images[0]

image.save("sd3_hello_world-no-T5.png")
```
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/pipelines/stable_diffusion/stable_diffusion_3.md