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import sys |
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model_name = sys.argv[1] |
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model_card = f"""--- |
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language: |
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- en |
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license: openrail++ |
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tags: |
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- stable-diffusion |
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- stable-diffusion-diffusers |
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- stable-diffusion-xl |
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- text-to-image |
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- art |
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- artistic |
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- diffusers |
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- anime |
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--- |
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# {model_name.split("/")[-1].replace("-", " ").capitalize()} |
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`{model_name}` is a Stable Diffusion model that has been fine-tuned on [stabilityai/stable-diffusion-xl-base-1.0](https://huggingface.co./stabilityai/stable-diffusion-xl-base-1.0). |
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Please consider supporting me: |
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- on [Patreon](https://www.patreon.com/Lykon275) |
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- or [buy me a coffee](https://snipfeed.co/lykon) |
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## Diffusers |
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For more general information on how to run text-to-image models with 🧨 Diffusers, see [the docs](https://huggingface.co./docs/diffusers/using-diffusers/conditional_image_generation). |
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1. Installation |
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``` |
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pip install diffusers transformers accelerate |
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``` |
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2. Run |
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```py |
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from diffusers import AutoPipelineForText2Image, DEISMultistepScheduler |
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import torch |
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pipe = AutoPipelineForText2Image.from_pretrained('{model_name}', torch_dtype=torch.float16, variant="fp16") |
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pipe.scheduler = DEISMultistepScheduler.from_config(pipe.scheduler.config) |
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pipe = pipe.to("cuda") |
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prompt = "portrait photo of muscular bearded guy in a worn mech suit, light bokeh, intricate, steel metal, elegant, sharp focus, soft lighting, vibrant colors" |
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generator = torch.manual_seed(0) |
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image = pipe(prompt, num_inference_steps=25).images[0] |
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image.save("./image.png") |
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``` |
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![](./image.png) |
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""" |
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from huggingface_hub import HfApi |
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api = HfApi() |
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read_me_path = "./README.md" |
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with open(read_me_path, "w") as f: |
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f.write(model_card) |
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api.upload_file( |
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path_or_fileobj=read_me_path, |
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path_in_repo=read_me_path, |
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repo_id=model_name, |
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repo_type="model", |
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) |
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from diffusers import AutoPipelineForText2Image, DEISMultistepScheduler |
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import torch |
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pipe = AutoPipelineForText2Image.from_pretrained(model_name, torch_dtype=torch.float16) |
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pipe.scheduler = DEISMultistepScheduler.from_config(pipe.scheduler.config) |
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pipe = pipe.to("cuda") |
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prompt = "portrait photo of muscular bearded guy in a worn mech suit, light bokeh, intricate, steel metal, elegant, sharp focus, soft lighting, vibrant colors" |
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generator = torch.manual_seed(0) |
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image = pipe(prompt, num_inference_steps=25).images[0] |
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image_path = "./image.png" |
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image.save(image_path) |
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api.upload_file( |
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path_or_fileobj=image_path, |
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path_in_repo=image_path, |
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repo_id=model_name, |
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repo_type="model", |
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) |
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pipe.push_to_hub(model_name, variant="fp16") |
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