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aad2ddd
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Parent(s):
d857e4f
Update app.py
Browse files
app.py
CHANGED
@@ -16,7 +16,6 @@ with open('loras.json', 'r') as f:
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# Initialize the base model
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base_model = "black-forest-labs/FLUX.1-dev"
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pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
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pipe.to("cuda")
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MAX_SEED = 2**32-1
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@@ -50,6 +49,7 @@ def update_selection(evt: gr.SelectData):
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@spaces.GPU(duration=80)
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def generate_image(prompt, trigger_word, steps, seed, cfg_scale, width, height, lora_scale, progress):
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generator = torch.Generator(device="cuda").manual_seed(seed)
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@@ -87,7 +87,7 @@ def run_lora(prompt, cfg_scale, steps, selected_index, randomize_seed, seed, wid
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seed = random.randint(0, MAX_SEED)
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image = generate_image(prompt, trigger_word, steps, seed, cfg_scale, width, height, lora_scale, progress)
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pipe.unload_lora_weights()
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return image, seed
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# Initialize the base model
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base_model = "black-forest-labs/FLUX.1-dev"
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pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
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MAX_SEED = 2**32-1
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@spaces.GPU(duration=80)
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def generate_image(prompt, trigger_word, steps, seed, cfg_scale, width, height, lora_scale, progress):
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pipe.to("cuda")
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generator = torch.Generator(device="cuda").manual_seed(seed)
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seed = random.randint(0, MAX_SEED)
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image = generate_image(prompt, trigger_word, steps, seed, cfg_scale, width, height, lora_scale, progress)
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pipe.to("cpu")
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pipe.unload_lora_weights()
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return image, seed
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