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Update app.py
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app.py
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@@ -2,39 +2,17 @@ from contextlib import nullcontext
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import gradio as gr
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import torch
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from torch import autocast
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from diffusers import StableDiffusionPipeline
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device = "cuda" if torch.cuda.is_available() else "cpu"
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context = autocast if device == "cuda" else nullcontext
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dtype = torch.float16 if device == "cuda" else torch.float32
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if device == "cuda":
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pipe = StableDiffusionPipeline.from_pretrained("lambdalabs/sd-naruto-diffusers", torch_dtype=dtype)
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else:
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pipe = StableDiffusionOnnxPipeline.from_pretrained(
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"lambdalabs/sd-naruto-diffusers",
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revision="onnx",
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provider="CPUExecutionProvider"
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)
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# onnx model revision not available
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except:
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pipe = StableDiffusionPipeline.from_pretrained("lambdalabs/sd-naruto-diffusers", torch_dtype=dtype)
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pipe = pipe.to(device)
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# Sometimes the nsfw checker is confused by the Naruto images, you can disable
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# it at your own risk here
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disable_safety = True
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if disable_safety:
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def null_safety(images, **kwargs):
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return images, False
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pipe.safety_checker = null_safety
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def infer(prompt, n_samples, steps, scale):
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@@ -129,19 +107,19 @@ block = gr.Blocks(css=css)
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examples = [
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[
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'
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2,
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7.5,
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],
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[
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'
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2,
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7.5,
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],
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[
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'
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2,
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7
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],
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]
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@@ -153,13 +131,9 @@ with block:
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<img class="logo" src="https://lambdalabs.com/hubfs/logos/lambda-logo.svg" alt="Lambda Logo"
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style="margin: auto; max-width: 7rem;">
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<h1 style="font-weight: 900; font-size: 3rem;">
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</h1>
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</div>
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<p style="margin-bottom: 10px; font-size: 94%">
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Generate new Naruto anime character from a text description,
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<a href="https://lambdalabs.com/blog/how-to-fine-tune-stable-diffusion-how-we-made-the-text-to-pokemon-model-at-lambda/">created by Lambda Labs</a>.
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</p>
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</div>
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"""
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)
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with gr.Row(elem_id="advanced-options"):
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samples = gr.Slider(label="Images", minimum=1, maximum=4, value=2, step=1)
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steps = gr.Slider(label="Steps", minimum=5, maximum=50, value=
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scale = gr.Slider(
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label="Guidance Scale", minimum=0, maximum=50, value=7.5, step=0.1
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)
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</p>
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</div>
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<div class="acknowledgments">
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<p> Put in a text prompt and generate your own
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<p> Here are some <a href="https://huggingface.co/lambdalabs/sd-naruto-diffusers">examples</a> of generated images.
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<p>If you want to find out how we made this model read about it in <a href="https://lambdalabs.com/blog/how-to-fine-tune-stable-diffusion-how-we-made-the-text-to-pokemon-model-at-lambda/">this blog post</a>.
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<p>And if you want to train your own Stable Diffusion variants, see our <a href="https://github.com/LambdaLabsML/examples/tree/main/stable-diffusion-finetuning">Examples Repo</a>!
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<p>Trained by Eole Cervenka at <a href="https://lambdalabs.com/">Lambda Labs</a>.</p>
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</div>
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"""
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import gradio as gr
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import torch
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from torch import autocast
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from diffusers import StableDiffusionPipeline
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device = "cuda" if torch.cuda.is_available() else "cpu"
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context = autocast if device == "cuda" else nullcontext
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dtype = torch.float16 if device == "cuda" else torch.float32
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model_id = 'eolecvk/dreambooth-avatar'
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pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=dtype)
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pipe = pipe.to(device)
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def infer(prompt, n_samples, steps, scale):
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examples = [
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[
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'Jeff Bezos, avatarart style person',
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2,
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7.5,
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],
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[
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'Elon Musk, avatarart style person',
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2,
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7.5,
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],
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[
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'Bill Gates, avatarart style person',
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2,
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7,
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],
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]
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<img class="logo" src="https://lambdalabs.com/hubfs/logos/lambda-logo.svg" alt="Lambda Logo"
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style="margin: auto; max-width: 7rem;">
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<h1 style="font-weight: 900; font-size: 3rem;">
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Avatar text to image
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</h1>
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</div>
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</div>
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"""
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)
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with gr.Row(elem_id="advanced-options"):
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samples = gr.Slider(label="Images", minimum=1, maximum=4, value=2, step=1)
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steps = gr.Slider(label="Steps", minimum=5, maximum=50, value=50, step=5)
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scale = gr.Slider(
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label="Guidance Scale", minimum=0, maximum=50, value=7.5, step=0.1
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)
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</p>
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</div>
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<div class="acknowledgments">
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<p> Put in a text prompt and generate your own Avatar art style image!
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<p>If you want to find out how we made this model read about it in <a href="https://lambdalabs.com/blog/how-to-fine-tune-stable-diffusion-how-we-made-the-text-to-pokemon-model-at-lambda/">this blog post</a>.
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<p>Trained by Eole Cervenka at <a href="https://lambdalabs.com/">Lambda Labs</a>.</p>
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</div>
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"""
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