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---
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](https://huggingface.co/Norod78/sd2-dreambooth-ClaymationXmas/tree/main/examples) folder for images generated with this model using a1111's WebUI
### WebUI Example Collage
```py
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](https://twitter.com/Norod78)
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