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add full training

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mi804
2026-04-24 15:11:34 +08:00
parent 3799bdc23a
commit 2d7d5137ea
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examples/stable_diffusion_xl/model_training/validate_full/stable-diffusion-xl-base-1.0.py Normal file
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from diffsynth.pipelines.stable_diffusion_xl import StableDiffusionXLPipeline, ModelConfig
from diffsynth.core import load_state_dict
import torch
pipe = StableDiffusionXLPipeline.from_pretrained(
torch_dtype=torch.float32,
model_configs=[
ModelConfig(model_id="stabilityai/stable-diffusion-xl-base-1.0", origin_file_pattern="text_encoder/model.safetensors"),
ModelConfig(model_id="stabilityai/stable-diffusion-xl-base-1.0", origin_file_pattern="text_encoder_2/model.safetensors"),
ModelConfig(model_id="stabilityai/stable-diffusion-xl-base-1.0", origin_file_pattern="unet/diffusion_pytorch_model.safetensors"),
ModelConfig(model_id="stabilityai/stable-diffusion-xl-base-1.0", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
],
tokenizer_config=ModelConfig(model_id="stabilityai/stable-diffusion-xl-base-1.0", origin_file_pattern="tokenizer/"),
tokenizer_2_config=ModelConfig(model_id="stabilityai/stable-diffusion-xl-base-1.0", origin_file_pattern="tokenizer_2/"),
)
state_dict = load_state_dict("./models/train/stable-diffusion-xl-base-1.0_full/epoch-1.safetensors", torch_dtype=torch.float32)
pipe.unet.load_state_dict(state_dict)
image = pipe(
prompt="a dog",
negative_prompt="",
cfg_scale=7.0,
height=1024,
width=1024,
seed=42,
num_inference_steps=50,
)
image.save("image_stable-diffusion-xl-base-1.0_full.jpg")