AlekseyCalvin commited on
Commit
714ba62
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verified ·
1 Parent(s): 44fba52

Update app.py

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Files changed (1) hide show
  1. app.py +9 -3
app.py CHANGED
@@ -48,8 +48,14 @@ with open('loras.json', 'r') as f:
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  #pipe = diffusers.ZImagePipeline.from_pretrained("Disty0/Z-Image-Turbo-SDNQ-uint4-svd-r32", torch_dtype=torch.bfloat16)
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  #torch.cuda.empty_cache()
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  #pipe = diffusers.ZImagePipeline.from_pretrained("dimitribarbot/Z-Image-Turbo-BF16", torch_dtype=torch.bfloat16)
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- pipe = diffusers.ZImagePipeline.from_pretrained("AlekseyCalvin/Z_Image_Deturbo_Diffusers", torch_dtype=torch.bfloat16)
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-
 
 
 
 
 
 
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  #pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taef1", torch_dtype=torch.float16).to("cuda")
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  #pipe.vae = AutoencoderKL.from_pretrained("AlekseyCalvin/Custom_VAE-Z-image-FLUX.1-by-G-REPA", torch_dtype=torch.bfloat16, device_map="cuda")
@@ -223,7 +229,7 @@ with gr.Blocks(css=css) as app:
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  with gr.Column():
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  with gr.Row():
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  cfg_scale = gr.Slider(label="CFG Scale", minimum=0, maximum=20, step=.1, value=1.0)
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- steps = gr.Slider(label="Steps", minimum=1, maximum=50, step=1, value=18)
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  with gr.Row():
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  width = gr.Slider(label="Width", minimum=256, maximum=1536, step=64, value=1024)
 
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  #pipe = diffusers.ZImagePipeline.from_pretrained("Disty0/Z-Image-Turbo-SDNQ-uint4-svd-r32", torch_dtype=torch.bfloat16)
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  #torch.cuda.empty_cache()
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  #pipe = diffusers.ZImagePipeline.from_pretrained("dimitribarbot/Z-Image-Turbo-BF16", torch_dtype=torch.bfloat16)
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+ #pipe = diffusers.ZImagePipeline.from_pretrained("AlekseyCalvin/Z_Image_Deturbo_Diffusers", torch_dtype=torch.bfloat16)
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+ qwen_path = 'nightknocker/recurrent-qwen3-z-image-turbo'
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+ text_encoder = RecurrentDecoderModel.from_pretrained(qwen_path).to(torch.bfloat16)
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+ pipeline = ZImagePipeline.from_pretrained(
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+ 'AlekseyCalvin/Z-Image-Deturbo-Returbo-Base_Diffusers',
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+ text_encoder=text_encoder,
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+ torch_dtype=torch.bfloat16
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+ )
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  #pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taef1", torch_dtype=torch.float16).to("cuda")
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  #pipe.vae = AutoencoderKL.from_pretrained("AlekseyCalvin/Custom_VAE-Z-image-FLUX.1-by-G-REPA", torch_dtype=torch.bfloat16, device_map="cuda")
 
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  with gr.Column():
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  with gr.Row():
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  cfg_scale = gr.Slider(label="CFG Scale", minimum=0, maximum=20, step=.1, value=1.0)
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+ steps = gr.Slider(label="Steps", minimum=1, maximum=50, step=1, value=10)
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  with gr.Row():
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  width = gr.Slider(label="Width", minimum=256, maximum=1536, step=64, value=1024)