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