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Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -34,12 +34,12 @@ from image_gen_aux import UpscaleWithModel
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#from diffusers.models.attention_processor import AttnProcessor2_0
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from transformers import CLIPTextModelWithProjection, CLIPTextModel, CLIPTokenizer
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torch.backends.cuda.matmul.allow_tf32 =
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torch.backends.cuda.matmul.allow_bf16_reduced_precision_reduction = False
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torch.backends.cuda.matmul.allow_fp16_reduced_precision_reduction = False
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torch.backends.cudnn.allow_tf32 =
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torch.backends.cudnn.deterministic = False
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torch.backends.cudnn.benchmark =
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torch.backends.cuda.preferred_blas_library="cublas"
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torch.backends.cuda.preferred_linalg_library="cusolver"
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@@ -118,8 +118,7 @@ model_repo='John6666/uber-realistic-porn-merge-xl-urpmxl-v6final-sdxl'
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#'John6666/pornworks-real-porn-ponyv04-sdxl'
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#'John6666/pornmaster-amateur-sdxlv1vae-sdxl'
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rv='ford442/RealVisXL_V5.0_BF16'
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text_encoder = CLIPTextModel.from_pretrained(rv, subfolder='text_encoder', token=True)#.to(device=device, dtype=torch.bfloat16)
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text_encoder_2 = CLIPTextModelWithProjection.from_pretrained(model_repo, subfolder='text_encoder_2',token=True)#.to(device=device, dtype=torch.bfloat16)
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#from diffusers.models.attention_processor import AttnProcessor2_0
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from transformers import CLIPTextModelWithProjection, CLIPTextModel, CLIPTokenizer
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torch.backends.cuda.matmul.allow_tf32 = True
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torch.backends.cuda.matmul.allow_bf16_reduced_precision_reduction = False
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torch.backends.cuda.matmul.allow_fp16_reduced_precision_reduction = False
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torch.backends.cudnn.allow_tf32 = True
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torch.backends.cudnn.deterministic = False
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torch.backends.cudnn.benchmark = True
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torch.backends.cuda.preferred_blas_library="cublas"
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torch.backends.cuda.preferred_linalg_library="cusolver"
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#'John6666/pornworks-real-porn-ponyv04-sdxl'
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#'John6666/pornmaster-amateur-sdxlv1vae-sdxl'
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rv='ford442/RealVisXL_V5.0_BF64'
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text_encoder = CLIPTextModel.from_pretrained(rv, subfolder='text_encoder', token=True)#.to(device=device, dtype=torch.bfloat16)
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text_encoder_2 = CLIPTextModelWithProjection.from_pretrained(model_repo, subfolder='text_encoder_2',token=True)#.to(device=device, dtype=torch.bfloat16)
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