metadata

license: creativeml-openrail-m
language:
  - en
thumbnail: >-
  https://huggingface.co/Norod78/sd2-dreambooth-ClaymationXmas/resolve/main/collage_1.jpeg
tags:
  - stable-diffusion
  - stable-diffusion-diffusers
  - text-to-image
datasets:
  - Norod78/ChristmasClaymation-blip-captions
inference: true
widget:
  - text: Whilly Wonka, ClaymationXmas
  - text: >-
      Pikachu, ClaymationXmas, very detailed, clean, high quality, sharp image,
      Naoto Hattori

sd2-dreambooth-ClaymationXmas

Use ClaymationXmas in your prompt

WebUI Examples

See examples folder for images generated with this model using a1111's WebUI

WebUI Example Collage


from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
import torch

def main():
    #////////////////////////////////////////////
    seed = 42
    model = "Norod78/sd2-dreambooth-ClaymationXmas"
    #////////////////////////////////////////////

    torch.manual_seed(seed)
    generator = torch.Generator()
    generator.manual_seed(seed)

    scheduler = DPMSolverMultistepScheduler(
        beta_start=0.00085,
        beta_end=0.012,
        beta_schedule="scaled_linear",
        num_train_timesteps=1000,
        trained_betas=None,
        predict_epsilon=True,
        thresholding=False,
        algorithm_type="dpmsolver++",
        solver_type="midpoint",
        lower_order_final=True,
)

    device = "cuda" if torch.cuda.is_available() else "cpu"
    dtype = torch.float16 if device == "cuda" else torch.float32
    pipe = StableDiffusionPipeline.from_pretrained(model, scheduler=scheduler,torch_dtype=dtype, generator=generator,use_auth_token=True).to(device)

    #////////////////////////////////////////////
    num_inference_steps = 20
    width=512
    height=512
    samples=4
    #////////////////////////////////////////////

    prompt = "Willy Wonka, ClaymationXmas"
    result = pipe([prompt] * samples, num_inference_steps=num_inference_steps, height=height, width=width)
    images = result["images"]
    for i, image in enumerate(images):       
        prompt_to_print = str(i) + "-" + prompt
        output_file = prompt_to_print.replace(" ", "_") + "-" + str(width) + "x" +str(height)+ "_" + str(num_inference_steps) + "steps" + "_seed" + str(seed) + ".jpg"
        image.save(output_file)
        print("Saved: " + str(output_file))

if __name__ == '__main__':
    main()

Fine Tuned by @Norod78