import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("dg845/DiffusionGemma-diffusers", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]diffusers-native checkpoint for the google/diffusiongemma-26B-A4B-it discrete diffusion LLM.
You can use the model as follows. Note that you need transformers>=5.12.0 for the underlying DiffusionGemmaForBlockDiffusion model.
import torch
from diffusers import DiffusionGemmaPipeline
pipe = DiffusionGemmaPipeline.from_pretrained(
"dg845/DiffusionGemma-diffusers",
torch_dtype=torch.bfloat16,
)
pipe.to("cuda")
# Compile the decoder model for faster inference
pipe.model.model.decoder = torch.compile(pipe.model.model.decoder, mode="reduce-overhead"),
output = pipe(
prompt="Why is the sky blue?",
gen_length=256,
num_inference_steps=48,
cache_implementation="static",
generator=torch.Generator("cuda").manual_seed(42),
)
print(output.texts[0])
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