Update app.py
Browse files
app.py
CHANGED
@@ -42,6 +42,9 @@ footer {
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repo_nsfw_classifier = pipeline("image-classification", model="Falconsai/nsfw_image_detection")
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repo_default = DiffusionPipeline.from_pretrained("fluently/Fluently-XL-Final", torch_dtype=torch.float16, use_safetensors=True, add_watermarker=False)
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# repo_large = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16, add_watermarker=False, revision="refs/pr/1")
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# repo_large.load_lora_weights("ehristoforu/dalle-3-xl-v2", adapter_name="base")
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@@ -51,7 +54,7 @@ repo_customs = {
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"Default": repo_default,
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# "Realistic": DiffusionPipeline.from_pretrained("ehristoforu/Visionix-alpha", torch_dtype=torch.float16, use_safetensors=True, add_watermarker=False),
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# "Anime": DiffusionPipeline.from_pretrained("cagliostrolab/animagine-xl-3.1", torch_dtype=torch.float16, use_safetensors=True, add_watermarker=False),
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# "Large": repo_neo,
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}
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@@ -71,7 +74,7 @@ def get_seed(seed):
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@spaces.GPU(duration=60)
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def generate(input=DEFAULT_INPUT, filter_input="", negative_input=DEFAULT_NEGATIVE_INPUT, model=DEFAULT_MODEL, height=DEFAULT_HEIGHT, width=DEFAULT_WIDTH, steps=1, guidance=0, number=1, seed=None):
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repo = repo_customs[model or "Default"]
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filter_input = filter_input or ""
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negative_input = negative_input or DEFAULT_NEGATIVE_INPUT
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steps_set = steps
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@@ -89,22 +92,14 @@ def generate(input=DEFAULT_INPUT, filter_input="", negative_input=DEFAULT_NEGATI
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elif model == "Pixel":
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steps_set = 15
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guidance_set = 1.5
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repo.load_lora_weights("artificialguybr/PixelArtRedmond", adapter_name="base")
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repo.load_lora_weights("nerijs/pixel-art-xl", adapter_name="base2")
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repo.set_adapters(["base", "base2"], adapter_weights=[1, 1])
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elif model == "Large":
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steps_set = 25
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guidance_set = 3.5
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else:
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steps_set = 25
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guidance_set = 7
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repo.load_lora_weights("ehristoforu/dalle-3-xl-v2", adapter_name="base")
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print(2)
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repo.set_adapters(["base"], adapter_weights=[0.7])
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print(3)
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repo.to(DEVICE)
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if not steps:
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steps = steps_set
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repo_nsfw_classifier = pipeline("image-classification", model="Falconsai/nsfw_image_detection")
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repo_default = DiffusionPipeline.from_pretrained("fluently/Fluently-XL-Final", torch_dtype=torch.float16, use_safetensors=True, add_watermarker=False)
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repo.load_lora_weights("ehristoforu/dalle-3-xl-v2", adapter_name="default_base")
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repo.load_lora_weights("artificialguybr/PixelArtRedmond", adapter_name="pixel_base")
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repo.load_lora_weights("nerijs/pixel-art-xl", adapter_name="pixel_base_2")
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# repo_large = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16, add_watermarker=False, revision="refs/pr/1")
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# repo_large.load_lora_weights("ehristoforu/dalle-3-xl-v2", adapter_name="base")
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"Default": repo_default,
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# "Realistic": DiffusionPipeline.from_pretrained("ehristoforu/Visionix-alpha", torch_dtype=torch.float16, use_safetensors=True, add_watermarker=False),
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# "Anime": DiffusionPipeline.from_pretrained("cagliostrolab/animagine-xl-3.1", torch_dtype=torch.float16, use_safetensors=True, add_watermarker=False),
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"Pixel": repo_default,
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# "Large": repo_neo,
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}
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@spaces.GPU(duration=60)
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def generate(input=DEFAULT_INPUT, filter_input="", negative_input=DEFAULT_NEGATIVE_INPUT, model=DEFAULT_MODEL, height=DEFAULT_HEIGHT, width=DEFAULT_WIDTH, steps=1, guidance=0, number=1, seed=None):
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repo = repo_customs[model or "Default"].to(DEVICE)
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filter_input = filter_input or ""
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negative_input = negative_input or DEFAULT_NEGATIVE_INPUT
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steps_set = steps
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elif model == "Pixel":
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steps_set = 15
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guidance_set = 1.5
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repo.set_adapters(["pixel_base", "pixel_base_2"], adapter_weights=[1, 1])
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elif model == "Large":
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steps_set = 25
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guidance_set = 3.5
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else:
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steps_set = 25
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guidance_set = 7
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repo.set_adapters(["default_base"], adapter_weights=[0.7])
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if not steps:
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steps = steps_set
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