import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("carlofkl/DreamLite-base", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]DreamLite
ByteDance's UNet-based text-to-image and image-edit diffusion model. 3-branch dual-CFG design, runs at 1024×1024.
import torch
from diffusers import DreamLitePipeline
pipe = DreamLitePipeline.from_pretrained(
"carlofkl/DreamLite-base", torch_dtype=torch.bfloat16
).to("cuda")
image = pipe("a corgi astronaut", num_inference_steps=28).images[0]
License: CC BY-NC 4.0 (non-commercial). A full model card will be added once the diffusers integration PR is merged.
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