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06a2f8e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 | import torch
from diffsynth.core import ModelConfig
from diffsynth.pipelines.stable_diffusion import StableDiffusionPipeline
vram_config = {
"offload_dtype": torch.float32,
"offload_device": "cpu",
"onload_dtype": torch.float32,
"onload_device": "cpu",
"preparing_dtype": torch.float32,
"preparing_device": "cuda",
"computation_dtype": torch.float32,
"computation_device": "cuda",
}
pipe = StableDiffusionPipeline.from_pretrained(
torch_dtype=torch.float32,
model_configs=[
ModelConfig(model_id="AI-ModelScope/stable-diffusion-v1-5", origin_file_pattern="text_encoder/model.safetensors", **vram_config),
ModelConfig(model_id="AI-ModelScope/stable-diffusion-v1-5", origin_file_pattern="unet/diffusion_pytorch_model.safetensors", **vram_config),
ModelConfig(model_id="AI-ModelScope/stable-diffusion-v1-5", origin_file_pattern="vae/diffusion_pytorch_model.safetensors", **vram_config),
],
tokenizer_config=ModelConfig(model_id="AI-ModelScope/stable-diffusion-v1-5", origin_file_pattern="tokenizer/"),
vram_limit=torch.cuda.mem_get_info("cuda")[1] / (1024 ** 3) - 0.5,
)
image = pipe(
prompt="a photo of an astronaut riding a horse on mars, high quality, detailed",
negative_prompt="blurry, low quality, deformed",
cfg_scale=7.5,
height=512,
width=512,
seed=42,
rand_device="cuda",
num_inference_steps=50,
)
image.save("image.jpg")
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