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* ernie-image pipeline * ernie-image inference and training * style fix * ernie docs * lowvram * final style fix * pr-review * pr-fix round2 * set uniform training weight * fix * update lowvram docs
25 lines
863 B
Python
25 lines
863 B
Python
from diffsynth.pipelines.ernie_image import ErnieImagePipeline, ModelConfig
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import torch
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pipe = ErnieImagePipeline.from_pretrained(
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torch_dtype=torch.bfloat16,
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device='cuda',
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model_configs=[
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ModelConfig(model_id="baidu/ERNIE-Image", origin_file_pattern="transformer/diffusion_pytorch_model*.safetensors"),
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ModelConfig(model_id="baidu/ERNIE-Image", origin_file_pattern="text_encoder/model.safetensors"),
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ModelConfig(model_id="baidu/ERNIE-Image", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
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],
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tokenizer_config=ModelConfig(model_id="baidu/ERNIE-Image", origin_file_pattern="tokenizer/"),
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)
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image = pipe(
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prompt="一只黑白相间的中华田园犬",
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negative_prompt="",
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height=1024,
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width=1024,
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seed=42,
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num_inference_steps=50,
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cfg_scale=4.0,
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)
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image.save("output.jpg")
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