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Update app.py
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app.py
CHANGED
@@ -39,9 +39,6 @@ def get_lora_sd_pipeline(
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pipe = StableDiffusionPipeline.from_pretrained(base_model_name_or_path, torch_dtype=dtype).to(device)
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pipe.unet = PeftModel.from_pretrained(pipe.unet, unet_sub_dir, adapter_name=adapter_name)
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pipe.unet.set_adapter(adapter_name)
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pipe.unet.set_peft_model_state_dict(
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{k: v*lora_scale for k, v in pipe.unet.state_dict().items()}
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)
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if os.path.exists(text_encoder_sub_dir):
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pipe.text_encoder = PeftModel.from_pretrained(
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@@ -102,7 +99,7 @@ def infer(
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pipe = pipe.to(device)
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prompt_embeds = encode_prompt(prompt, pipe.tokenizer, pipe.text_encoder)
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negative_prompt_embeds = encode_prompt(negative_prompt, pipe.tokenizer, pipe.text_encoder)
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image = pipe(
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prompt_embeds=prompt_embeds,
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pipe = StableDiffusionPipeline.from_pretrained(base_model_name_or_path, torch_dtype=dtype).to(device)
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pipe.unet = PeftModel.from_pretrained(pipe.unet, unet_sub_dir, adapter_name=adapter_name)
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pipe.unet.set_adapter(adapter_name)
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if os.path.exists(text_encoder_sub_dir):
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pipe.text_encoder = PeftModel.from_pretrained(
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pipe = pipe.to(device)
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prompt_embeds = encode_prompt(prompt, pipe.tokenizer, pipe.text_encoder)
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negative_prompt_embeds = encode_prompt(negative_prompt, pipe.tokenizer, pipe.text_encoder)
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pipe.fuse_lora(lora_scale=lora_scale)
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image = pipe(
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prompt_embeds=prompt_embeds,
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