* `max_sequence_length` cannot be more than 256.
* `guidance_scale` needs to be 0.
* As this is a timestep-distilled model, it benefits from fewer sampling steps.  
```python
import torch
from diffusers import FluxPipeline

pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16)
pipe.enable_model_cpu_offload()

prompt = "A cat holding a sign that says hello world"
out = pipe(
prompt=prompt,
guidance_scale=0.,
height=768,
width=1360,
num_inference_steps=4,
max_sequence_length=256,
).images[0]
out.save("image.png")
```
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/pipelines/flux.md