import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("tlwu/tiny-random-flux", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]This pipeline is intended for debugging or testing. It is saved from black-forest-labs/FLUX.1-dev with smaller size and randomly initialized parameters.
Example Usage
import torch
from diffusers import FluxPipeline
pipe = FluxPipeline.from_pretrained("tlwu/tiny-random-flux", torch_dtype=torch.bfloat16)
prompt = "a tree with blue leaves"
image = pipe(
prompt,
height=1024,
width=1024,
guidance_scale=3.5,
num_inference_steps=50,
max_sequence_length=512,
generator=torch.Generator("cpu").manual_seed(0)
).images[0]
image.save("test.png")
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