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1 Parent(s): ac9b18f

Update app.py

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  1. app.py +1 -1
app.py CHANGED
@@ -38,7 +38,7 @@ taef1 = AutoencoderTiny.from_pretrained("madebyollin/taef1", torch_dtype=dtype).
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  good_vae = AutoencoderKL.from_pretrained(base_model, subfolder="vae", torch_dtype=dtype).to(device)
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  txt2img_pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=dtype).to(device)
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- # txt2img_pipe.__class__.load_lora_into_transformer = classmethod(load_lora_into_transformer)
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  # img2img model
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  img2img_pipe = AutoPipelineForImage2Image.from_pretrained(base_model, vae=good_vae, transformer=txt2img_pipe.transformer, text_encoder=txt2img_pipe.text_encoder, tokenizer=txt2img_pipe.tokenizer, text_encoder_2=txt2img_pipe.text_encoder_2, tokenizer_2=txt2img_pipe.tokenizer_2, torch_dtype=dtype)
 
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  good_vae = AutoencoderKL.from_pretrained(base_model, subfolder="vae", torch_dtype=dtype).to(device)
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  txt2img_pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=dtype).to(device)
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+ txt2img_pipe.__class__.load_lora_into_transformer = classmethod(load_lora_into_transformer)
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  # img2img model
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  img2img_pipe = AutoPipelineForImage2Image.from_pretrained(base_model, vae=good_vae, transformer=txt2img_pipe.transformer, text_encoder=txt2img_pipe.text_encoder, tokenizer=txt2img_pipe.tokenizer, text_encoder_2=txt2img_pipe.text_encoder_2, tokenizer_2=txt2img_pipe.tokenizer_2, torch_dtype=dtype)